export const dataTree={
  "code": 200,
  "message": "",
  "detail": "",
  "data": [
      {
          "id": 1,
          "name": "datasource",
          "sequence": 1,
          "description": "数据读取",
          "create_ts": 1645515710,
          "create_time": "2022-02-22 15:41:50",
          "is_enable": true,
          "nodes": [],
          "resources": [
              {
                  "id": 18,
                  "name": "read_url",
                  "description": [
                      "读取导入数据"
                  ],
                  "create_ts": 1688564533,
                  "create_time": "2023-07-05 21:42:13",
                  "update_ts": 1688987987,
                  "update_time": "2023-07-10 19:19:47",
                  "label": "导入数据",
                  "icon": "",
                  "category_id": 1,
                  "is_enable": true,
                  "operator": {
                      "id": 72,
                      "name": "read_url",
                      "description": [
                          "读取导入数据"
                      ],
                      "create_ts": 1688987987,
                      "create_time": "2023-07-10 19:19:47",
                      "update_ts": 1688987987,
                      "update_time": "2023-07-10 19:19:47",
                      "input_num": 0,
                      "output_num": 1,
                      "icon": "",
                      "category_id": 1,
                      "doc_url": "docs/canvas_operator/data_source/read_url",
                      "version": "1.1.1",
                      "is_enable": true,
                      "template_id": 18,
                      "package_label": "pandas",
                      "function_label": "pandas",
                      "run_function": "run",
                      "run_filepath": "main.py",
                      "language_name": "python",
                      "framework_name": null,
                      "stage_name": "开发",
                      "language_code": "python",
                      "framework_code": null,
                      "stage_code": "dev",
                      "inputs": [],
                      "outputs": [
                          {
                              "id": 135,
                              "name": "resultdata",
                              "description": [
                                  "返回数据。"
                              ],
                              "sequence": 1,
                              "value_type_code": "dataframe",
                              "value_type_name": "数据帧",
                              "label": "数据"
                          }
                      ],
                      "configs": {
                          "default": {
                              "label": "默认",
                              "results": [
                                  {
                                      "label": "默认",
                                      "results": [
                                          {
                                              "id": 162,
                                              "name": "url",
                                              "description": [
                                                  "选择文件地址"
                                              ],
                                              "sequence": 1,
                                              "label": "文件地址",
                                              "default_value": null,
                                              "value_type_code": "string",
                                              "value_type_name": "字符串",
                                              "is_required": true,
                                              "is_visible": true,
                                              "is_editable": true,
                                              "is_enable": true,
                                              "ui_type_code": "uploadFile",
                                              "ui_type_name": "uploadFile",
                                              "ui_config": null,
                                              "section_sequence": 0
                                          }
                                      ]
                                  }
                              ]
                          },
                          "runtime": {
                              "label": "运行期间",
                              "results": []
                          },
                          "framework": {
                              "label": "框架",
                              "results": []
                          },
                          "section": {
                              "label": "自定义",
                              "results": []
                          }
                      },
                      "tags": [
                          {
                              "id": 144,
                              "tag_name": "数据源",
                              "create_time": "2023-07-10 19:19:47",
                              "tag_id": 86
                          },
                          {
                              "id": 145,
                              "tag_name": "数据读取",
                              "create_time": "2023-07-10 19:19:47",
                              "tag_id": 87
                          }
                      ],
                      "storages": {
                          "artifact": false,
                          "model": false,
                          "data": false
                      },
                      "upstreams": {
                          "except": [
                              "datasource",
                              "data_preprocessing",
                              "data_visualization",
                              "statistical_analysis",
                              "feature_engineering",
                              "ml",
                              "evaluate_model",
                              "platform_function",
                              "custom"
                          ],
                          "only": null
                      },
                      "downstreams": {
                          "except": [
                              "datasource",
                              "evaluate_model"
                          ],
                          "only": null
                      },
                      "category_name": "datasource",
                      "label": "导入数据"
                  },
                  "sequence": 0,
                  "is_delete": false,
                  "delete_ts": null,
                  "delete_time": null,
                  "source_type_code": "official",
                  "source_type_name": "官方"
              },
              {
                  "id": 55,
                  "name": "read_url2",
                  "description": [
                      "读取导入数据"
                  ],
                  "create_ts": 1689216752,
                  "create_time": "2023-07-13 10:52:32",
                  "update_ts": 1689252438,
                  "update_time": "2023-07-13 20:47:18",
                  "label": "导入数据2",
                  "icon": "",
                  "category_id": 1,
                  "is_enable": true,
                  "operator": {
                      "id": 114,
                      "name": "read_url2",
                      "description": [
                          "读取导入数据"
                      ],
                      "create_ts": 1689252438,
                      "create_time": "2023-07-13 20:47:18",
                      "update_ts": 1689252438,
                      "update_time": "2023-07-13 20:47:18",
                      "input_num": 0,
                      "output_num": 1,
                      "icon": "",
                      "category_id": 1,
                      "doc_url": "docs/canvas_operator/data_source/read_url",
                      "version": "1.1.5",
                      "is_enable": true,
                      "template_id": 55,
                      "package_label": "pandas",
                      "function_label": "pandas",
                      "run_function": "run",
                      "run_filepath": "main.py",
                      "language_name": "python",
                      "framework_name": null,
                      "stage_name": "开发",
                      "language_code": "python",
                      "framework_code": null,
                      "stage_code": "dev",
                      "inputs": [],
                      "outputs": [
                          {
                              "id": 212,
                              "name": "resultdata",
                              "description": [
                                  "返回数据。"
                              ],
                              "sequence": 1,
                              "value_type_code": "dataframe",
                              "value_type_name": "数据帧",
                              "label": "数据"
                          }
                      ],
                      "configs": {
                          "default": {
                              "label": "默认",
                              "results": [
                                  {
                                      "label": "默认",
                                      "results": [
                                          {
                                              "id": 290,
                                              "name": "url",
                                              "description": [
                                                  "选择文件地址"
                                              ],
                                              "sequence": 1,
                                              "label": "文件地址",
                                              "default_value": null,
                                              "value_type_code": "string",
                                              "value_type_name": "字符串",
                                              "is_required": true,
                                              "is_visible": true,
                                              "is_editable": true,
                                              "is_enable": true,
                                              "ui_type_code": "uploadFile",
                                              "ui_type_name": "uploadFile",
                                              "ui_config": null,
                                              "section_sequence": 0
                                          }
                                      ]
                                  }
                              ]
                          },
                          "runtime": {
                              "label": "运行期间",
                              "results": []
                          },
                          "framework": {
                              "label": "框架",
                              "results": []
                          },
                          "section": {
                              "label": "自定义",
                              "results": []
                          }
                      },
                      "tags": [
                          {
                              "id": 225,
                              "tag_name": "数据源",
                              "create_time": "2023-07-13 20:47:18",
                              "tag_id": 86
                          },
                          {
                              "id": 226,
                              "tag_name": "数据读取",
                              "create_time": "2023-07-13 20:47:18",
                              "tag_id": 87
                          }
                      ],
                      "storages": {
                          "artifact": false,
                          "model": false,
                          "data": false
                      },
                      "upstreams": {
                          "except": [
                              "datasource",
                              "data_preprocessing",
                              "data_visualization",
                              "statistical_analysis",
                              "feature_engineering",
                              "ml",
                              "evaluate_model",
                              "platform_function",
                              "custom"
                          ],
                          "only": null
                      },
                      "downstreams": {
                          "except": [
                              "datasource",
                              "evaluate_model"
                          ],
                          "only": null
                      },
                      "category_name": "datasource",
                      "label": "导入数据2"
                  },
                  "sequence": 0,
                  "is_delete": false,
                  "delete_ts": null,
                  "delete_time": null,
                  "source_type_code": "official",
                  "source_type_name": "官方"
              }
          ],
          "resources_total": 2
      },
      {
          "id": 2,
          "name": "data_preprocessing",
          "sequence": 2,
          "description": "数据预处理",
          "create_ts": 1645515710,
          "create_time": "2022-02-22 15:41:50",
          "is_enable": true,
          "nodes": [],
          "resources": [
              {
                  "id": 1,
                  "name": "data_type_conversion",
                  "description": [
                      "该算法提供数据类型转换功能；",
                      "基于str、float和int等进行数据类型转换；",
                      "其中，若将str转为数字类型，则需确保原数据符合数字类型特征或者使用特征处理等将变量转为数字类型。"
                  ],
                  "create_ts": 1688564532,
                  "create_time": "2023-07-05 21:42:12",
                  "update_ts": 1688987985,
                  "update_time": "2023-07-10 19:19:45",
                  "label": "类型转换",
                  "icon": "",
                  "category_id": 2,
                  "is_enable": true,
                  "operator": {
                      "id": 55,
                      "name": "data_type_conversion",
                      "description": [
                          "该算法提供数据类型转换功能；",
                          "基于str、float和int等进行数据类型转换；",
                          "其中，若将str转为数字类型，则需确保原数据符合数字类型特征或者使用特征处理等将变量转为数字类型。"
                      ],
                      "create_ts": 1688987985,
                      "create_time": "2023-07-10 19:19:45",
                      "update_ts": 1688987985,
                      "update_time": "2023-07-10 19:19:45",
                      "input_num": 1,
                      "output_num": 3,
                      "icon": "",
                      "category_id": 2,
                      "doc_url": "docs/canvas_operator/data_preprocessing/type_conversion",
                      "version": "1.0.1",
                      "is_enable": true,
                      "template_id": 1,
                      "package_label": "pandas",
                      "function_label": "pandas",
                      "run_function": "run",
                      "run_filepath": "main.py",
                      "language_name": "python",
                      "framework_name": null,
                      "stage_name": "开发",
                      "language_code": "python",
                      "framework_code": null,
                      "stage_code": "dev",
                      "inputs": [
                          {
                              "id": 104,
                              "name": "inputTable",
                              "description": [
                                  "数据"
                              ],
                              "sequence": 1,
                              "value_type_code": "dataframe",
                              "value_type_name": "数据帧",
                              "label": "数据"
                          }
                      ],
                      "outputs": [
                          {
                              "id": 105,
                              "name": "raw_column_types",
                              "description": [
                                  "原矩阵数据类型"
                              ],
                              "sequence": 1,
                              "value_type_code": "dataframe",
                              "value_type_name": "数据帧",
                              "label": "原矩阵数据类型"
                          },
                          {
                              "id": 106,
                              "name": "column_types",
                              "description": [
                                  "原矩阵数据类型"
                              ],
                              "sequence": 2,
                              "value_type_code": "dataframe",
                              "value_type_name": "数据帧",
                              "label": "生成矩阵数据类型"
                          },
                          {
                              "id": 107,
                              "name": "resultdata",
                              "description": [
                                  "生成数据"
                              ],
                              "sequence": 3,
                              "value_type_code": "dataframe",
                              "value_type_name": "数据帧",
                              "label": "生成数据"
                          }
                      ],
                      "configs": {
                          "default": {
                              "label": "默认",
                              "results": []
                          },
                          "runtime": {
                              "label": "运行期间",
                              "results": []
                          },
                          "framework": {
                              "label": "框架",
                              "results": []
                          },
                          "section": {
                              "label": "自定义",
                              "results": [
                                  {
                                      "label": "基础参数",
                                      "results": [
                                          {
                                              "id": 143,
                                              "name": "reserveOldFeat",
                                              "description": [
                                                  "是否覆盖原数据"
                                              ],
                                              "sequence": 1,
                                              "label": "转换后数据列是否覆盖原数据列",
                                              "default_value": null,
                                              "value_type_code": "string",
                                              "value_type_name": "字符串",
                                              "is_required": true,
                                              "is_visible": true,
                                              "is_editable": true,
                                              "is_enable": true,
                                              "ui_type_code": "radio",
                                              "ui_type_name": "radio",
                                              "ui_config": {
                                                  "options": [
                                                      {
                                                          "label": "是",
                                                          "value": "True"
                                                      },
                                                      {
                                                          "label": "否",
                                                          "value": "False"
                                                      }
                                                  ]
                                              },
                                              "section_sequence": 1
                                          },
                                          {
                                              "id": 144,
                                              "name": "selectedFilter",
                                              "description": [
                                                  "选择要进行条件筛选的特征列，通过<列>选择参数，通过<类型>选择条件，填写<值>选择所需对比的参数值（包括float，int，str），通过<运算符>选择多个条件之间的合并关系，<单位>按需填写。",
                                                  "若覆盖原数据的参数值，则不需要填写'单位'值。",
                                                  "若不覆盖原数据的参数值，则需要填写'单位'值。",
                                                  "若属性对象类型为非数值型离散字符串（Object）,不支持类型类型转换节点。"
                                              ],
                                              "sequence": 2,
                                              "label": "指定转换变量以及转换条件",
                                              "default_value": null,
                                              "value_type_code": "list",
                                              "value_type_name": "列表",
                                              "is_required": true,
                                              "is_visible": true,
                                              "is_editable": true,
                                              "is_enable": true,
                                              "ui_type_code": "conditionUnitScreen",
                                              "ui_type_name": "conditionUnitScreen",
                                              "ui_config": null,
                                              "section_sequence": 1
                                          }
                                      ]
                                  }
                              ]
                          }
                      },
                      "tags": [
                          {
                              "id": 108,
                              "tag_name": "数据预处理",
                              "create_time": "2023-07-10 19:19:45",
                              "tag_id": 66
                          },
                          {
                              "id": 109,
                              "tag_name": "类型转换",
                              "create_time": "2023-07-10 19:19:45",
                              "tag_id": 67
                          }
                      ],
                      "storages": {
                          "artifact": false,
                          "model": false,
                          "data": false
                      },
                      "upstreams": {
                          "except": [
                              "data_visualization",
                              "ml",
                              "evaluate_model"
                          ],
                          "only": null
                      },
                      "downstreams": {
                          "except": [
                              "datasource"
                          ],
                          "only": null
                      },
                      "category_name": "data_preprocessing",
                      "label": "类型转换"
                  },
                  "sequence": 0,
                  "is_delete": false,
                  "delete_ts": null,
                  "delete_time": null,
                  "source_type_code": "official",
                  "source_type_name": "官方"
              },
              {
                  "id": 2,
                  "name": "matrix_operations_filtering",
                  "description": [
                      "矩阵过滤可以对数据按照目标属性列表进行筛选，生成一个新的目标矩阵。"
                  ],
                  "create_ts": 1688564532,
                  "create_time": "2023-07-05 21:42:12",
                  "update_ts": 1688987985,
                  "update_time": "2023-07-10 19:19:45",
                  "label": "矩阵过滤",
                  "icon": "",
                  "category_id": 2,
                  "is_enable": true,
                  "operator": {
                      "id": 56,
                      "name": "matrix_operations_filtering",
                      "description": [
                          "矩阵过滤可以对数据按照目标属性列表进行筛选，生成一个新的目标矩阵。"
                      ],
                      "create_ts": 1688987985,
                      "create_time": "2023-07-10 19:19:45",
                      "update_ts": 1688987985,
                      "update_time": "2023-07-10 19:19:45",
                      "input_num": 1,
                      "output_num": 1,
                      "icon": "",
                      "category_id": 2,
                      "doc_url": "docs/canvas_operator/data_preprocessing/matrix_operations_filtering",
                      "version": "1.0.1",
                      "is_enable": true,
                      "template_id": 2,
                      "package_label": "pandas",
                      "function_label": "DataFrame",
                      "run_function": "run",
                      "run_filepath": "main.py",
                      "language_name": "python",
                      "framework_name": null,
                      "stage_name": "开发",
                      "language_code": "python",
                      "framework_code": null,
                      "stage_code": "dev",
                      "inputs": [
                          {
                              "id": 108,
                              "name": "inputTable",
                              "description": [
                                  "数据"
                              ],
                              "sequence": 1,
                              "value_type_code": "dataframe",
                              "value_type_name": "数据帧",
                              "label": "数据"
                          }
                      ],
                      "outputs": [
                          {
                              "id": 109,
                              "name": "resultdata",
                              "description": [
                                  "数据矩阵过滤后的数据。"
                              ],
                              "sequence": 1,
                              "value_type_code": "dataframe",
                              "value_type_name": "数据帧",
                              "label": "生成数据"
                          }
                      ],
                      "configs": {
                          "default": {
                              "label": "默认",
                              "results": []
                          },
                          "runtime": {
                              "label": "运行期间",
                              "results": []
                          },
                          "framework": {
                              "label": "框架",
                              "results": []
                          },
                          "section": {
                              "label": "自定义",
                              "results": [
                                  {
                                      "label": "方法1",
                                      "results": [
                                          {
                                              "id": 145,
                                              "name": "selectedColNames",
                                              "description": [
                                                  "选择筛选的特征列，无数量限制。"
                                              ],
                                              "sequence": 1,
                                              "label": "筛选指定列",
                                              "default_value": null,
                                              "value_type_code": "list",
                                              "value_type_name": "列表",
                                              "is_required": false,
                                              "is_visible": true,
                                              "is_editable": true,
                                              "is_enable": true,
                                              "ui_type_code": "dynamicParameter",
                                              "ui_type_name": "dynamicParameter",
                                              "ui_config": null,
                                              "section_sequence": 1
                                          }
                                      ]
                                  },
                                  {
                                      "label": "方法2",
                                      "results": [
                                          {
                                              "id": 146,
                                              "name": "selectedFilter",
                                              "description": [
                                                  "选择要进行条件筛选的特征列，通过<列>选择参数，通过<类型>选择条件，填写<值>选择所需对比的参数值（该值自定义填写），通过<运算符>选择多个条件之间的合并关系。"
                                              ],
                                              "sequence": 1,
                                              "label": "依据条件筛选指定列",
                                              "default_value": null,
                                              "value_type_code": "list",
                                              "value_type_name": "列表",
                                              "is_required": false,
                                              "is_visible": true,
                                              "is_editable": true,
                                              "is_enable": true,
                                              "ui_type_code": "conditionScreen",
                                              "ui_type_name": "conditionScreen",
                                              "ui_config": null,
                                              "section_sequence": 2
                                          }
                                      ]
                                  }
                              ]
                          }
                      },
                      "tags": [
                          {
                              "id": 110,
                              "tag_name": "数据预处理",
                              "create_time": "2023-07-10 19:19:45",
                              "tag_id": 66
                          },
                          {
                              "id": 111,
                              "tag_name": "矩阵过滤",
                              "create_time": "2023-07-10 19:19:45",
                              "tag_id": 68
                          }
                      ],
                      "storages": {
                          "artifact": false,
                          "model": false,
                          "data": false
                      },
                      "upstreams": {
                          "except": [
                              "data_visualization",
                              "ml",
                              "evaluate_model"
                          ],
                          "only": null
                      },
                      "downstreams": {
                          "except": [
                              "datasource"
                          ],
                          "only": null
                      },
                      "category_name": "data_preprocessing",
                      "label": "矩阵过滤"
                  },
                  "sequence": 0,
                  "is_delete": false,
                  "delete_ts": null,
                  "delete_time": null,
                  "source_type_code": "official",
                  "source_type_name": "官方"
              },
              {
                  "id": 3,
                  "name": "matrix_operations_merge",
                  "description": [
                      "合并算法组件是将两张表的数据按行/列合并，需要表的行/列数保持一致。"
                  ],
                  "create_ts": 1688564532,
                  "create_time": "2023-07-05 21:42:12",
                  "update_ts": 1688987985,
                  "update_time": "2023-07-10 19:19:45",
                  "label": "矩阵合并",
                  "icon": "",
                  "category_id": 2,
                  "is_enable": true,
                  "operator": {
                      "id": 57,
                      "name": "matrix_operations_merge",
                      "description": [
                          "合并算法组件是将两张表的数据按行/列合并，需要表的行/列数保持一致。"
                      ],
                      "create_ts": 1688987985,
                      "create_time": "2023-07-10 19:19:45",
                      "update_ts": 1688987985,
                      "update_time": "2023-07-10 19:19:45",
                      "input_num": 2,
                      "output_num": 1,
                      "icon": "",
                      "category_id": 2,
                      "doc_url": "docs/canvas_operator/data_preprocessing/matrix_operations_merge",
                      "version": "1.0.1",
                      "is_enable": true,
                      "template_id": 3,
                      "package_label": "pandas",
                      "function_label": "concat",
                      "run_function": "run",
                      "run_filepath": "main.py",
                      "language_name": "python",
                      "framework_name": null,
                      "stage_name": "开发",
                      "language_code": "python",
                      "framework_code": null,
                      "stage_code": "dev",
                      "inputs": [
                          {
                              "id": 110,
                              "name": "inputTable1",
                              "description": [
                                  "待合并的数据矩阵"
                              ],
                              "sequence": 1,
                              "value_type_code": "dataframe",
                              "value_type_name": "数据帧",
                              "label": "待合并矩阵1"
                          },
                          {
                              "id": 111,
                              "name": "inputTable2",
                              "description": [
                                  "待合并的数据矩阵"
                              ],
                              "sequence": 2,
                              "value_type_code": "dataframe",
                              "value_type_name": "数据帧",
                              "label": "待合并矩阵2"
                          }
                      ],
                      "outputs": [
                          {
                              "id": 112,
                              "name": "resultdata",
                              "description": [
                                  "连接后的数据矩阵"
                              ],
                              "sequence": 1,
                              "value_type_code": "dataframe",
                              "value_type_name": "数据帧",
                              "label": "连接后矩阵"
                          }
                      ],
                      "configs": {
                          "default": {
                              "label": "默认",
                              "results": [
                                  {
                                      "label": "默认",
                                      "results": [
                                          {
                                              "id": 147,
                                              "name": "selectedAxis",
                                              "description": [
                                                  "选择矩阵连接方式，可选项包含行连接，列连接。"
                                              ],
                                              "sequence": 1,
                                              "label": "选择连接方式",
                                              "default_value": null,
                                              "value_type_code": "int",
                                              "value_type_name": "整型",
                                              "is_required": true,
                                              "is_visible": true,
                                              "is_editable": true,
                                              "is_enable": true,
                                              "ui_type_code": "radio",
                                              "ui_type_name": "radio",
                                              "ui_config": {
                                                  "options": [
                                                      {
                                                          "label": "行连接",
                                                          "value": 0
                                                      },
                                                      {
                                                          "label": "列连接",
                                                          "value": 1
                                                      }
                                                  ]
                                              },
                                              "section_sequence": 0
                                          }
                                      ]
                                  }
                              ]
                          },
                          "runtime": {
                              "label": "运行期间",
                              "results": []
                          },
                          "framework": {
                              "label": "框架",
                              "results": []
                          },
                          "section": {
                              "label": "自定义",
                              "results": []
                          }
                      },
                      "tags": [
                          {
                              "id": 112,
                              "tag_name": "数据预处理",
                              "create_time": "2023-07-10 19:19:45",
                              "tag_id": 66
                          },
                          {
                              "id": 113,
                              "tag_name": "矩阵连接",
                              "create_time": "2023-07-10 19:19:45",
                              "tag_id": 69
                          }
                      ],
                      "storages": {
                          "artifact": false,
                          "model": false,
                          "data": false
                      },
                      "upstreams": {
                          "except": [
                              "data_visualization",
                              "ml",
                              "evaluate_model"
                          ],
                          "only": null
                      },
                      "downstreams": {
                          "except": [
                              "datasource"
                          ],
                          "only": null
                      },
                      "category_name": "data_preprocessing",
                      "label": "矩阵合并"
                  },
                  "sequence": 0,
                  "is_delete": false,
                  "delete_ts": null,
                  "delete_time": null,
                  "source_type_code": "official",
                  "source_type_name": "官方"
              },
              {
                  "id": 4,
                  "name": "matrix_operations_split",
                  "description": [
                      "拆分算子会将算子按照这个比例/数据个数拆分成两份数据，这个值代表第一份数据占输入数据的比例。"
                  ],
                  "create_ts": 1688564532,
                  "create_time": "2023-07-05 21:42:12",
                  "update_ts": 1688987985,
                  "update_time": "2023-07-10 19:19:45",
                  "label": "矩阵拆分",
                  "icon": "",
                  "category_id": 2,
                  "is_enable": true,
                  "operator": {
                      "id": 58,
                      "name": "matrix_operations_split",
                      "description": [
                          "拆分算子会将算子按照这个比例/数据个数拆分成两份数据，这个值代表第一份数据占输入数据的比例。"
                      ],
                      "create_ts": 1688987985,
                      "create_time": "2023-07-10 19:19:45",
                      "update_ts": 1688987985,
                      "update_time": "2023-07-10 19:19:45",
                      "input_num": 1,
                      "output_num": 2,
                      "icon": "",
                      "category_id": 2,
                      "doc_url": "docs/canvas_operator/data_preprocessing/matrix_operations_split",
                      "version": "1.0.1",
                      "is_enable": true,
                      "template_id": 4,
                      "package_label": "pandas",
                      "function_label": "hsplit",
                      "run_function": "run",
                      "run_filepath": "main.py",
                      "language_name": "python",
                      "framework_name": null,
                      "stage_name": "开发",
                      "language_code": "python",
                      "framework_code": null,
                      "stage_code": "dev",
                      "inputs": [
                          {
                              "id": 113,
                              "name": "inputTable",
                              "description": [
                                  "数据"
                              ],
                              "sequence": 1,
                              "value_type_code": "dataframe",
                              "value_type_name": "数据帧",
                              "label": "数据"
                          }
                      ],
                      "outputs": [
                          {
                              "id": 114,
                              "name": "Table1",
                              "description": [
                                  "拆分数据集1"
                              ],
                              "sequence": 1,
                              "value_type_code": "dataframe",
                              "value_type_name": "数据帧",
                              "label": "拆分数据集1"
                          },
                          {
                              "id": 115,
                              "name": "Table2",
                              "description": [
                                  "拆分数据集2"
                              ],
                              "sequence": 2,
                              "value_type_code": "dataframe",
                              "value_type_name": "数据帧",
                              "label": "拆分数据集2"
                          }
                      ],
                      "configs": {
                          "default": {
                              "label": "默认",
                              "results": []
                          },
                          "runtime": {
                              "label": "运行期间",
                              "results": []
                          },
                          "framework": {
                              "label": "框架",
                              "results": []
                          },
                          "section": {
                              "label": "自定义",
                              "results": [
                                  {
                                      "label": "拆分数据集",
                                      "results": [
                                          {
                                              "id": 148,
                                              "name": "fraction",
                                              "description": [
                                                  "此比率表示发送到第一个输出数据集的行的百分比，因此必须输入一个介于0和1之间的小数。",
                                                  "取值范围为(0,1)。"
                                              ],
                                              "sequence": 1,
                                              "label": "拆分比例",
                                              "default_value": "0.7",
                                              "value_type_code": "float",
                                              "value_type_name": "浮点数",
                                              "is_required": true,
                                              "is_visible": true,
                                              "is_editable": true,
                                              "is_enable": true,
                                              "ui_type_code": "slider",
                                              "ui_type_name": "slider",
                                              "ui_config": {
                                                  "min": 0,
                                                  "max": 1,
                                                  "step": 0.01,
                                                  "unitText": "比例参数"
                                              },
                                              "section_sequence": 1
                                          },
                                          {
                                              "id": 149,
                                              "name": "randomSeed",
                                              "description": [
                                                  "随机数生成器的种子数，保证每次生成的随机数序列相同，方便调参和结果重现。如果不设置该参数，则每次运行结果可能不同。",
                                                  "取值范围为正整数，请输入非负整数值以启动要使用的实例的伪随机序列。"
                                              ],
                                              "sequence": 2,
                                              "label": "随机数种子",
                                              "default_value": "1",
                                              "value_type_code": "int",
                                              "value_type_name": "整型",
                                              "is_required": false,
                                              "is_visible": true,
                                              "is_editable": true,
                                              "is_enable": true,
                                              "ui_type_code": "input",
                                              "ui_type_name": "input",
                                              "ui_config": null,
                                              "section_sequence": 1
                                          }
                                      ]
                                  }
                              ]
                          }
                      },
                      "tags": [
                          {
                              "id": 114,
                              "tag_name": "数据预处理",
                              "create_time": "2023-07-10 19:19:45",
                              "tag_id": 66
                          },
                          {
                              "id": 115,
                              "tag_name": "拆分",
                              "create_time": "2023-07-10 19:19:45",
                              "tag_id": 70
                          }
                      ],
                      "storages": {
                          "artifact": false,
                          "model": false,
                          "data": false
                      },
                      "upstreams": {
                          "except": [
                              "data_visualization",
                              "ml",
                              "evaluate_model"
                          ],
                          "only": null
                      },
                      "downstreams": {
                          "except": [
                              "datasource"
                          ],
                          "only": null
                      },
                      "category_name": "data_preprocessing",
                      "label": "矩阵拆分"
                  },
                  "sequence": 0,
                  "is_delete": false,
                  "delete_ts": null,
                  "delete_time": null,
                  "source_type_code": "official",
                  "source_type_name": "官方"
              },
              {
                  "id": 5,
                  "name": "missvalue_fill",
                  "description": [
                      "数据模型中，可能存在一些字段存在空值。",
                      "替换缺失值算子支持将缺失的数据替换为该列的最大/最小/平均值、或自定义值。"
                  ],
                  "create_ts": 1688564532,
                  "create_time": "2023-07-05 21:42:12",
                  "update_ts": 1688987985,
                  "update_time": "2023-07-10 19:19:45",
                  "label": "缺失值填充",
                  "icon": "",
                  "category_id": 2,
                  "is_enable": true,
                  "operator": {
                      "id": 59,
                      "name": "missvalue_fill",
                      "description": [
                          "数据模型中，可能存在一些字段存在空值。",
                          "替换缺失值算子支持将缺失的数据替换为该列的最大/最小/平均值、或自定义值。"
                      ],
                      "create_ts": 1688987985,
                      "create_time": "2023-07-10 19:19:45",
                      "update_ts": 1688987985,
                      "update_time": "2023-07-10 19:19:45",
                      "input_num": 1,
                      "output_num": 1,
                      "icon": "",
                      "category_id": 2,
                      "doc_url": "docs/canvas_operator/data_preprocessing/missvalue_fill",
                      "version": "1.0.1",
                      "is_enable": true,
                      "template_id": 5,
                      "package_label": "pandas",
                      "function_label": "fillna",
                      "run_function": "run",
                      "run_filepath": "main.py",
                      "language_name": "python",
                      "framework_name": null,
                      "stage_name": "开发",
                      "language_code": "python",
                      "framework_code": null,
                      "stage_code": "dev",
                      "inputs": [
                          {
                              "id": 116,
                              "name": "inputTable",
                              "description": [
                                  "数据"
                              ],
                              "sequence": 1,
                              "value_type_code": "dataframe",
                              "value_type_name": "数据帧",
                              "label": "数据"
                          }
                      ],
                      "outputs": [
                          {
                              "id": 117,
                              "name": "resultdata",
                              "description": [
                                  "填充某个固定值/默认值后的矩阵数据"
                              ],
                              "sequence": 1,
                              "value_type_code": "dataframe",
                              "value_type_name": "数据帧",
                              "label": "生成数据"
                          }
                      ],
                      "configs": {
                          "default": {
                              "label": "默认",
                              "results": [
                                  {
                                      "label": "默认",
                                      "results": [
                                          {
                                              "id": 150,
                                              "name": "selectedColName",
                                              "description": [
                                                  "待填充字段"
                                              ],
                                              "sequence": 1,
                                              "label": "待填充字段",
                                              "default_value": null,
                                              "value_type_code": "list",
                                              "value_type_name": "列表",
                                              "is_required": false,
                                              "is_visible": true,
                                              "is_editable": true,
                                              "is_enable": true,
                                              "ui_type_code": "dynamicParameter",
                                              "ui_type_name": "dynamicParameter",
                                              "ui_config": {
                                                  "limit_num": 1
                                              },
                                              "section_sequence": 0
                                          }
                                      ]
                                  }
                              ]
                          },
                          "runtime": {
                              "label": "运行期间",
                              "results": []
                          },
                          "framework": {
                              "label": "框架",
                              "results": []
                          },
                          "section": {
                              "label": "自定义",
                              "results": [
                                  {
                                      "label": "参数",
                                      "results": [
                                          {
                                              "id": 151,
                                              "name": "replace_value",
                                              "description": [
                                                  "选取数据缺失值填充方式，可以选择min（最小值），max（最大值），mean（均值）或自定义值，若属性为离散对象（Object）,仅支持设置自定义值方式。"
                                              ],
                                              "sequence": 1,
                                              "label": "填充规则",
                                              "default_value": null,
                                              "value_type_code": "string",
                                              "value_type_name": "字符串",
                                              "is_required": false,
                                              "is_visible": true,
                                              "is_editable": true,
                                              "is_enable": true,
                                              "ui_type_code": "radio",
                                              "ui_type_name": "radio",
                                              "ui_config": {
                                                  "options": [
                                                      {
                                                          "label": "min",
                                                          "value": "min"
                                                      },
                                                      {
                                                          "label": "max",
                                                          "value": "max"
                                                      },
                                                      {
                                                          "label": "mean",
                                                          "value": "mean"
                                                      }
                                                  ],
                                                  "custom": true
                                              },
                                              "section_sequence": 1
                                          }
                                      ]
                                  }
                              ]
                          }
                      },
                      "tags": [
                          {
                              "id": 116,
                              "tag_name": "数据预处理",
                              "create_time": "2023-07-10 19:19:45",
                              "tag_id": 66
                          },
                          {
                              "id": 117,
                              "tag_name": "缺失值",
                              "create_time": "2023-07-10 19:19:45",
                              "tag_id": 71
                          }
                      ],
                      "storages": {
                          "artifact": false,
                          "model": false,
                          "data": false
                      },
                      "upstreams": {
                          "except": [
                              "data_visualization",
                              "ml",
                              "evaluate_model"
                          ],
                          "only": null
                      },
                      "downstreams": {
                          "except": [
                              "datasource"
                          ],
                          "only": null
                      },
                      "category_name": "data_preprocessing",
                      "label": "缺失值填充"
                  },
                  "sequence": 0,
                  "is_delete": false,
                  "delete_ts": null,
                  "delete_time": null,
                  "source_type_code": "official",
                  "source_type_name": "官方"
              },
              {
                  "id": 6,
                  "name": "sample_random",
                  "description": [
                      "随机采样算法组件按照给定的比例或者数目，对输入进行随机采样，每次采样是各自独立的。"
                  ],
                  "create_ts": 1688564532,
                  "create_time": "2023-07-05 21:42:12",
                  "update_ts": 1688987985,
                  "update_time": "2023-07-10 19:19:45",
                  "label": "采样-随机采样",
                  "icon": "",
                  "category_id": 2,
                  "is_enable": true,
                  "operator": {
                      "id": 60,
                      "name": "sample_random",
                      "description": [
                          "随机采样算法组件按照给定的比例或者数目，对输入进行随机采样，每次采样是各自独立的。"
                      ],
                      "create_ts": 1688987985,
                      "create_time": "2023-07-10 19:19:45",
                      "update_ts": 1688987985,
                      "update_time": "2023-07-10 19:19:45",
                      "input_num": 1,
                      "output_num": 1,
                      "icon": "",
                      "category_id": 2,
                      "doc_url": "docs/canvas_operator/data_preprocessing/sample_random",
                      "version": "1.0.1",
                      "is_enable": true,
                      "template_id": 6,
                      "package_label": "pandas",
                      "function_label": "sample",
                      "run_function": "run",
                      "run_filepath": "main.py",
                      "language_name": "python",
                      "framework_name": null,
                      "stage_name": "开发",
                      "language_code": "python",
                      "framework_code": null,
                      "stage_code": "dev",
                      "inputs": [
                          {
                              "id": 118,
                              "name": "inputTable",
                              "description": [
                                  "数据"
                              ],
                              "sequence": 1,
                              "value_type_code": "dataframe",
                              "value_type_name": "数据帧",
                              "label": "数据"
                          }
                      ],
                      "outputs": [
                          {
                              "id": 119,
                              "name": "resultdata",
                              "description": [
                                  "随机采样后的生成矩阵数据。"
                              ],
                              "sequence": 1,
                              "value_type_code": "dataframe",
                              "value_type_name": "数据帧",
                              "label": "生成矩阵"
                          }
                      ],
                      "configs": {
                          "default": {
                              "label": "默认",
                              "results": []
                          },
                          "runtime": {
                              "label": "运行期间",
                              "results": []
                          },
                          "framework": {
                              "label": "框架",
                              "results": []
                          },
                          "section": {
                              "label": "自定义",
                              "results": [
                                  {
                                      "label": "通过设定样本数值进行采样工作",
                                      "results": [
                                          {
                                              "id": 152,
                                              "name": "selectedNum",
                                              "description": [
                                                  "自定义采样数，采样数不能超过样本总数，可设置为0。同时，样本数值采样和样本比例采样只能选择一处进行特征选择。"
                                              ],
                                              "sequence": 1,
                                              "label": "采样数",
                                              "default_value": null,
                                              "value_type_code": "int",
                                              "value_type_name": "整型",
                                              "is_required": false,
                                              "is_visible": true,
                                              "is_editable": true,
                                              "is_enable": true,
                                              "ui_type_code": "inputNumber",
                                              "ui_type_name": "inputNumber",
                                              "ui_config": {
                                                  "min": 0,
                                                  "max": 999999,
                                                  "step": 1
                                              },
                                              "section_sequence": 1
                                          }
                                      ]
                                  },
                                  {
                                      "label": "通过设定样本比例进行采样工作",
                                      "results": [
                                          {
                                              "id": 153,
                                              "name": "selectedFrac",
                                              "description": [
                                                  "自定义采样比例值，采样比例值范围为（0,1），可设置为0。同时，样本数值采样和样本比例采样只能选择一处进行特征选择。"
                                              ],
                                              "sequence": 1,
                                              "label": "采样比例",
                                              "default_value": null,
                                              "value_type_code": "float",
                                              "value_type_name": "浮点数",
                                              "is_required": false,
                                              "is_visible": true,
                                              "is_editable": true,
                                              "is_enable": true,
                                              "ui_type_code": "slider",
                                              "ui_type_name": "slider",
                                              "ui_config": {
                                                  "min": 0,
                                                  "max": 1,
                                                  "step": 0.01,
                                                  "unitText": "比例值"
                                              },
                                              "section_sequence": 2
                                          }
                                      ]
                                  }
                              ]
                          }
                      },
                      "tags": [
                          {
                              "id": 118,
                              "tag_name": "数据预处理",
                              "create_time": "2023-07-10 19:19:45",
                              "tag_id": 66
                          },
                          {
                              "id": 119,
                              "tag_name": "采样",
                              "create_time": "2023-07-10 19:19:45",
                              "tag_id": 72
                          },
                          {
                              "id": 120,
                              "tag_name": "随机采样",
                              "create_time": "2023-07-10 19:19:45",
                              "tag_id": 73
                          }
                      ],
                      "storages": {
                          "artifact": false,
                          "model": false,
                          "data": false
                      },
                      "upstreams": {
                          "except": [
                              "data_visualization",
                              "ml",
                              "evaluate_model"
                          ],
                          "only": null
                      },
                      "downstreams": {
                          "except": [
                              "datasource"
                          ],
                          "only": null
                      },
                      "category_name": "data_preprocessing",
                      "label": "采样-随机采样"
                  },
                  "sequence": 0,
                  "is_delete": false,
                  "delete_ts": null,
                  "delete_time": null,
                  "source_type_code": "official",
                  "source_type_name": "官方"
              },
              {
                  "id": 7,
                  "name": "sort_order",
                  "description": [
                      "对数组重新进行顺序排序。"
                  ],
                  "create_ts": 1688564532,
                  "create_time": "2023-07-05 21:42:12",
                  "update_ts": 1688987985,
                  "update_time": "2023-07-10 19:19:45",
                  "label": "排序-按属性值顺序排序",
                  "icon": "",
                  "category_id": 2,
                  "is_enable": true,
                  "operator": {
                      "id": 61,
                      "name": "sort_order",
                      "description": [
                          "对数组重新进行顺序排序。"
                      ],
                      "create_ts": 1688987985,
                      "create_time": "2023-07-10 19:19:45",
                      "update_ts": 1688987985,
                      "update_time": "2023-07-10 19:19:45",
                      "input_num": 1,
                      "output_num": 1,
                      "icon": "",
                      "category_id": 2,
                      "doc_url": "docs/canvas_operator/data_preprocessing/sort_order",
                      "version": "1.0.1",
                      "is_enable": true,
                      "template_id": 7,
                      "package_label": "pandas",
                      "function_label": "sort_values",
                      "run_function": "run",
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                      "在实际分析过程中可以通过热图发现质量离谱的数据，协助进行质量控制。"
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                                  "data": false
                              },
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                              },
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                              },
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                          },
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                          "delete_time": null,
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                          "source_type_name": "官方"
                      },
                      {
                          "id": 25,
                          "name": "dim_reduction_pca",
                          "description": [
                              "主成分分析（PCA）是研究如何通过少数主成分揭示多个变量间的内部结构，考察多个变量间相关性的一种多元统计方法。",
                              "PCA从原始变量中导出少数主成分，使它们尽可能多地保留原始变量的信息，并且彼此间互不相关，作为新的综合指标。"
                          ],
                          "create_ts": 1688564533,
                          "create_time": "2023-07-05 21:42:13",
                          "update_ts": 1688987987,
                          "update_time": "2023-07-10 19:19:47",
                          "label": "降维-pca",
                          "icon": "",
                          "category_id": 501,
                          "is_enable": true,
                          "operator": {
                              "id": 79,
                              "name": "dim_reduction_pca",
                              "description": [
                                  "主成分分析（PCA）是研究如何通过少数主成分揭示多个变量间的内部结构，考察多个变量间相关性的一种多元统计方法。",
                                  "PCA从原始变量中导出少数主成分，使它们尽可能多地保留原始变量的信息，并且彼此间互不相关，作为新的综合指标。"
                              ],
                              "create_ts": 1688987987,
                              "create_time": "2023-07-10 19:19:47",
                              "update_ts": 1688987987,
                              "update_time": "2023-07-10 19:19:47",
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                              "output_num": 1,
                              "icon": "",
                              "category_id": 501,
                              "doc_url": "docs/canvas_operator/feature_engineering/dim_reduction_pca",
                              "version": "1.0.1",
                              "is_enable": true,
                              "template_id": 25,
                              "package_label": "scikit-learn",
                              "function_label": "PCA",
                              "run_function": "run",
                              "run_filepath": "main.py",
                              "language_name": "python",
                              "framework_name": null,
                              "stage_name": "开发",
                              "language_code": "python",
                              "framework_code": null,
                              "stage_code": "dev",
                              "inputs": [
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                                      "description": [
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                                      "sequence": 1,
                                      "value_type_code": "dataframe",
                                      "value_type_name": "数据帧",
                                      "label": "数据"
                                  }
                              ],
                              "outputs": [
                                  {
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                                      "name": "resultdata",
                                      "description": [
                                          "标准化之后的数据"
                                      ],
                                      "sequence": 1,
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                                      "value_type_name": "数据帧",
                                      "label": "数据"
                                  }
                              ],
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                                          {
                                              "label": "默认",
                                              "results": [
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                                                      "name": "selectedColNum",
                                                      "description": "导出主成分参数个数。",
                                                      "sequence": 1,
                                                      "label": "主成分特征数量",
                                                      "default_value": null,
                                                      "value_type_code": "int",
                                                      "value_type_name": "整型",
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                                                      "is_enable": true,
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                                                      "ui_type_name": "inputNumber",
                                                      "ui_config": {
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                                                          "max": 999999,
                                                          "step": 1
                                                      },
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                                                  }
                                              ]
                                          }
                                      ]
                                  },
                                  "runtime": {
                                      "label": "运行期间",
                                      "results": []
                                  },
                                  "framework": {
                                      "label": "框架",
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                                  },
                                  "section": {
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                                      "results": []
                                  }
                              },
                              "tags": [
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                                      "id": 159,
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                                  },
                                  {
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                                  }
                              ],
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                                  "data": false
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                              },
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                          "source_type_code": "official",
                          "source_type_name": "官方"
                      },
                      {
                          "id": 26,
                          "name": "discretization_binarization",
                          "description": [
                              "根据某一阈值，将数据分成两类，得到一个只拥有两个值域的二值化数据集。"
                          ],
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                          "create_time": "2023-07-05 21:42:13",
                          "update_ts": 1688987987,
                          "update_time": "2023-07-10 19:19:47",
                          "label": "离散化-二值化",
                          "icon": "",
                          "category_id": 501,
                          "is_enable": true,
                          "operator": {
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                              "name": "discretization_binarization",
                              "description": [
                                  "根据某一阈值，将数据分成两类，得到一个只拥有两个值域的二值化数据集。"
                              ],
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                              "create_time": "2023-07-10 19:19:47",
                              "update_ts": 1688987987,
                              "update_time": "2023-07-10 19:19:47",
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                              "package_label": "scikit-learn",
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                              "language_name": "python",
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                              "language_code": "python",
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                              "stage_code": "dev",
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                                      "sequence": 1,
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                                      "value_type_name": "数据帧",
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                              ],
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                                      "name": "resultdata",
                                      "description": [
                                          "离散化后的返回数据"
                                      ],
                                      "sequence": 1,
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                                      "label": "数据"
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                              ],
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                                              "label": "默认",
                                              "results": [
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                                                      "description": [
                                                          "根据某一阈值，将数据分成两类"
                                                      ],
                                                      "sequence": 1,
                                                      "label": "筛选特征列阈值条件",
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                                                      "value_type_code": "list",
                                                      "value_type_name": "列表",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "conditionUnitScreen",
                                                      "ui_type_name": "conditionUnitScreen",
                                                      "ui_config": null,
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                                                  }
                                              ]
                                          }
                                      ]
                                  },
                                  "runtime": {
                                      "label": "运行期间",
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                                  },
                                  "framework": {
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                                  },
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                              },
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                                      "id": 161,
                                      "tag_name": "特征工程",
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                                      "tag_id": 95
                                  },
                                  {
                                      "id": 160,
                                      "tag_name": "离散化-二值化",
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                                      "tag_id": 98
                                  }
                              ],
                              "storages": {
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                                  "data": false
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                          "source_type_name": "官方"
                      },
                      {
                          "id": 27,
                          "name": "encoder_onehot",
                          "description": [
                              "one-hot编码，也称独热编码，对于每一个特征，如果它有m个可能值，那么经过独热编码后，就变成了m个二元特征。",
                              "此外，这些特征互斥，每次只有一个激活。因此，经过独热编码后数据会变成稀疏的，输出结果为稀疏结构。"
                          ],
                          "create_ts": 1688564534,
                          "create_time": "2023-07-05 21:42:14",
                          "update_ts": 1688987988,
                          "update_time": "2023-07-10 19:19:48",
                          "label": "编码-onehot",
                          "icon": "",
                          "category_id": 501,
                          "is_enable": true,
                          "operator": {
                              "id": 81,
                              "name": "encoder_onehot",
                              "description": [
                                  "one-hot编码，也称独热编码，对于每一个特征，如果它有m个可能值，那么经过独热编码后，就变成了m个二元特征。",
                                  "此外，这些特征互斥，每次只有一个激活。因此，经过独热编码后数据会变成稀疏的，输出结果为稀疏结构。"
                              ],
                              "create_ts": 1688987988,
                              "create_time": "2023-07-10 19:19:48",
                              "update_ts": 1688987988,
                              "update_time": "2023-07-10 19:19:48",
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                              "output_num": 3,
                              "icon": "",
                              "category_id": 501,
                              "doc_url": "docs/canvas_operator/feature_engineering/encoder_onehot",
                              "version": "1.0.1",
                              "is_enable": true,
                              "template_id": 27,
                              "package_label": "scikit-learn",
                              "function_label": "OneHotEncoder",
                              "run_function": "run",
                              "run_filepath": "main.py",
                              "language_name": "python",
                              "framework_name": null,
                              "stage_name": "开发",
                              "language_code": "python",
                              "framework_code": null,
                              "stage_code": "dev",
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                                      ],
                                      "sequence": 1,
                                      "value_type_code": "dataframe",
                                      "value_type_name": "数据帧",
                                      "label": "数据"
                                  }
                              ],
                              "outputs": [
                                  {
                                      "id": 159,
                                      "name": "mapping_mat",
                                      "description": [
                                          "编码映射矩阵"
                                      ],
                                      "sequence": 1,
                                      "value_type_code": "dataframe",
                                      "value_type_name": "数据帧",
                                      "label": "映射矩阵"
                                  },
                                  {
                                      "id": 160,
                                      "name": "new_result",
                                      "description": [
                                          "编码后参数矩阵"
                                      ],
                                      "sequence": 2,
                                      "value_type_code": "dataframe",
                                      "value_type_name": "数据帧",
                                      "label": "编码后参数矩阵"
                                  },
                                  {
                                      "id": 161,
                                      "name": "resultdata",
                                      "description": [
                                          "编码后生成的矩阵数据"
                                      ],
                                      "sequence": 3,
                                      "value_type_code": "dataframe",
                                      "value_type_name": "数据帧",
                                      "label": "生成矩阵"
                                  }
                              ],
                              "configs": {
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                                      "results": [
                                          {
                                              "label": "默认",
                                              "results": [
                                                  {
                                                      "id": 176,
                                                      "name": "selectedColName",
                                                      "description": "选择待转换的特征目标列，进行独热编码转换，每次仅能选择一个。",
                                                      "sequence": 1,
                                                      "label": "选择待转换的目标列",
                                                      "default_value": null,
                                                      "value_type_code": "list",
                                                      "value_type_name": "列表",
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                                                      "is_visible": true,
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                                                      "is_enable": true,
                                                      "ui_type_code": "dynamicParameter",
                                                      "ui_type_name": "dynamicParameter",
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                                                  }
                                              ]
                                          }
                                      ]
                                  },
                                  "runtime": {
                                      "label": "运行期间",
                                      "results": []
                                  },
                                  "framework": {
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                                      "results": []
                                  },
                                  "section": {
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                                  }
                              },
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                                      "create_time": "2023-07-10 19:19:48",
                                      "tag_id": 95
                                  },
                                  {
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                                      "tag_name": "编码",
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                                      "tag_id": 99
                                  }
                              ],
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                          "source_type_code": "official",
                          "source_type_name": "官方"
                      },
                      {
                          "id": 28,
                          "name": "encoder_ordinal",
                          "description": [
                              "顺序编码把每一个特征变换成有序的整数数字特征(0到n-1)。"
                          ],
                          "create_ts": 1688564534,
                          "create_time": "2023-07-05 21:42:14",
                          "update_ts": 1688987988,
                          "update_time": "2023-07-10 19:19:48",
                          "label": "编码-数值化顺序",
                          "icon": "",
                          "category_id": 501,
                          "is_enable": true,
                          "operator": {
                              "id": 82,
                              "name": "encoder_ordinal",
                              "description": [
                                  "顺序编码把每一个特征变换成有序的整数数字特征(0到n-1)。"
                              ],
                              "create_ts": 1688987988,
                              "create_time": "2023-07-10 19:19:48",
                              "update_ts": 1688987988,
                              "update_time": "2023-07-10 19:19:48",
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                              "output_num": 1,
                              "icon": "",
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                              "doc_url": "docs/canvas_operator/feature_engineering/encoder_ordinal",
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                              "template_id": 28,
                              "package_label": "scikit-learn",
                              "function_label": "OrdinalEncoder",
                              "run_function": "run",
                              "run_filepath": "main.py",
                              "language_name": "python",
                              "framework_name": null,
                              "stage_name": "开发",
                              "language_code": "python",
                              "framework_code": null,
                              "stage_code": "dev",
                              "inputs": [
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                                      "name": "inputTable",
                                      "description": [
                                          "数据"
                                      ],
                                      "sequence": 1,
                                      "value_type_code": "dataframe",
                                      "value_type_name": "数据帧",
                                      "label": "数据"
                                  }
                              ],
                              "outputs": [
                                  {
                                      "id": 163,
                                      "name": "resultdata",
                                      "description": [
                                          "顺序编码后的新数据矩阵"
                                      ],
                                      "sequence": 1,
                                      "value_type_code": "dataframe",
                                      "value_type_name": "数据帧",
                                      "label": "数据"
                                  }
                              ],
                              "configs": {
                                  "default": {
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                                      "results": [
                                          {
                                              "label": "默认",
                                              "results": [
                                                  {
                                                      "id": 177,
                                                      "name": "selectedColNames",
                                                      "description": "选择相关特征列，可多选。",
                                                      "sequence": 1,
                                                      "label": "选择待编码的特征列",
                                                      "default_value": null,
                                                      "value_type_code": "list",
                                                      "value_type_name": "列表",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "dynamicParameter",
                                                      "ui_type_name": "dynamicParameter",
                                                      "ui_config": null,
                                                      "section_sequence": 0
                                                  }
                                              ]
                                          }
                                      ]
                                  },
                                  "runtime": {
                                      "label": "运行期间",
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                                  },
                                  "framework": {
                                      "label": "框架",
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                                  },
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                              },
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                                  },
                                  {
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                                      "tag_name": "编码",
                                      "create_time": "2023-07-10 19:19:48",
                                      "tag_id": 99
                                  },
                                  {
                                      "id": 165,
                                      "tag_name": "数值化",
                                      "create_time": "2023-07-10 19:19:48",
                                      "tag_id": 100
                                  },
                                  {
                                      "id": 166,
                                      "tag_name": "顺序编码",
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                                      "tag_id": 101
                                  }
                              ],
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                      }
                  ],
                  "resources_total": 7
              },
              {
                  "id": 502,
                  "name": "feature_importance",
                  "sequence": 2,
                  "description": "特征重要性评估",
                  "create_ts": 1645515710,
                  "create_time": "2022-02-22 15:41:50",
                  "is_enable": true,
                  "nodes": [],
                  "resources": [
                      {
                          "id": 19,
                          "name": "feature_analysis_DiscreteValue",
                          "description": [
                              "离散值为孤立的点集，非连续。",
                              "离散值特征分析统计离散特征的分布情况。",
                              "CondEntropy,当CondEntropy值最小时，说明选取该特征作为分类依据效果最优，即该特征对分类结果影响最大，因此该特征的重要性最高。",
                              "EntropyGain,当EntropyGain值最大时，表示通过这个特征进行划分能够减小样本的不确定度最大，即该特征是最重要的。",
                              "EntroyGainRatio, 此指标与信息增益类似，将熵增益标准化，可以避免认为某一特征比其它特征更重要。当EntropyGainRatio最大时，表明该特征对分类具有更好的区分度和分类准确性，即该特征较为重要。",
                              "DiscreteCorr,当两个特征之间的相关性较高时，说明其中某个特征可能对目标变量产生直接的影响，即这个特征的重要性较高。",
                              "Gini,与信息熵和基尼系数有关的算法，如决策树可使用的CART（Classification and Regression Trees），当Gini系数最小时，说明选取该特征作为分类依据效果最优，即该特征对分类结果影响最大，因此该特征的重要性最高。"
                          ],
                          "create_ts": 1688564533,
                          "create_time": "2023-07-05 21:42:13",
                          "update_ts": 1688987987,
                          "update_time": "2023-07-10 19:19:47",
                          "label": "离散值特征分析",
                          "icon": "",
                          "category_id": 502,
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                          "operator": {
                              "id": 73,
                              "name": "feature_analysis_DiscreteValue",
                              "description": [
                                  "离散值为孤立的点集，非连续。",
                                  "离散值特征分析统计离散特征的分布情况。",
                                  "CondEntropy,当CondEntropy值最小时，说明选取该特征作为分类依据效果最优，即该特征对分类结果影响最大，因此该特征的重要性最高。",
                                  "EntropyGain,当EntropyGain值最大时，表示通过这个特征进行划分能够减小样本的不确定度最大，即该特征是最重要的。",
                                  "EntroyGainRatio, 此指标与信息增益类似，将熵增益标准化，可以避免认为某一特征比其它特征更重要。当EntropyGainRatio最大时，表明该特征对分类具有更好的区分度和分类准确性，即该特征较为重要。",
                                  "DiscreteCorr,当两个特征之间的相关性较高时，说明其中某个特征可能对目标变量产生直接的影响，即这个特征的重要性较高。",
                                  "Gini,与信息熵和基尼系数有关的算法，如决策树可使用的CART（Classification and Regression Trees），当Gini系数最小时，说明选取该特征作为分类依据效果最优，即该特征对分类结果影响最大，因此该特征的重要性最高。"
                              ],
                              "create_ts": 1688987987,
                              "create_time": "2023-07-10 19:19:47",
                              "update_ts": 1688987987,
                              "update_time": "2023-07-10 19:19:47",
                              "input_num": 1,
                              "output_num": 2,
                              "icon": "",
                              "category_id": 502,
                              "doc_url": "docs/canvas_operator/feature_engineering/feature_analysis_DiscreteValue",
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                              "is_enable": true,
                              "template_id": 19,
                              "package_label": "scikit-learn",
                              "function_label": "wai_feature_analysis_DiscreteValue",
                              "run_function": "run",
                              "run_filepath": "main.py",
                              "language_name": "python",
                              "framework_name": null,
                              "stage_name": "开发",
                              "language_code": "python",
                              "framework_code": null,
                              "stage_code": "dev",
                              "inputs": [
                                  {
                                      "id": 136,
                                      "name": "inputTable",
                                      "description": [
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                                      "sequence": 1,
                                      "value_type_code": "dataframe",
                                      "value_type_name": "数据帧",
                                      "label": "数据"
                                  }
                              ],
                              "outputs": [
                                  {
                                      "id": 137,
                                      "name": "index_result",
                                      "description": [
                                          "返回各变量对应指标值矩阵"
                                      ],
                                      "sequence": 1,
                                      "value_type_code": "dataframe",
                                      "value_type_name": "数据帧",
                                      "label": "各变量对应指标值"
                                  },
                                  {
                                      "id": 138,
                                      "name": "resultdata",
                                      "description": [
                                          "返回经过指标变量筛选的矩阵"
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                                      "sequence": 2,
                                      "value_type_code": "dataframe",
                                      "value_type_name": "数据帧",
                                      "label": "生成矩阵"
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                              ],
                              "configs": {
                                  "default": {
                                      "label": "默认",
                                      "results": [
                                          {
                                              "label": "默认",
                                              "results": [
                                                  {
                                                      "id": 163,
                                                      "name": "labelColName",
                                                      "description": "选择筛选的目标列。",
                                                      "sequence": 1,
                                                      "label": "选择计算目标变量",
                                                      "default_value": null,
                                                      "value_type_code": "list",
                                                      "value_type_name": "列表",
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                                                      "is_visible": true,
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                                                      "is_enable": true,
                                                      "ui_type_code": "dynamicParameter",
                                                      "ui_type_name": "dynamicParameter",
                                                      "ui_config": {
                                                          "limit_num": 1
                                                      },
                                                      "section_sequence": 0
                                                  },
                                                  {
                                                      "id": 164,
                                                      "name": "featureColNames",
                                                      "description": "选择相关特征列，数量无限制。",
                                                      "sequence": 2,
                                                      "label": "选择待与目标变量相计算的变量列",
                                                      "default_value": null,
                                                      "value_type_code": "list",
                                                      "value_type_name": "列表",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "dynamicParameter",
                                                      "ui_type_name": "dynamicParameter",
                                                      "ui_config": null,
                                                      "section_sequence": 0
                                                  },
                                                  {
                                                      "id": 165,
                                                      "name": "chose_filter",
                                                      "description": [
                                                          "选择要进行条件筛选的特征列，通过<列>选择参数，通过<类型>选择条件，填写<值>选择所需对比的参数值（该值自定义填写），通过<运算符>选择多个条件之间的合并关系。"
                                                      ],
                                                      "sequence": 3,
                                                      "label": "依据条件筛选保留特征列",
                                                      "default_value": null,
                                                      "value_type_code": "list",
                                                      "value_type_name": "列表",
                                                      "is_required": false,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "conditionScreen",
                                                      "ui_type_name": "conditionScreen",
                                                      "ui_config": null,
                                                      "section_sequence": 0
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                                      ]
                                  },
                                  "runtime": {
                                      "label": "运行期间",
                                      "results": []
                                  },
                                  "framework": {
                                      "label": "框架",
                                      "results": []
                                  },
                                  "section": {
                                      "label": "自定义",
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                              },
                              "tags": [
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                                      "id": 146,
                                      "tag_name": "离散值特征分析",
                                      "create_time": "2023-07-10 19:19:47",
                                      "tag_id": 88
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                                  {
                                      "id": 147,
                                      "tag_name": "特征重要性评估",
                                      "create_time": "2023-07-10 19:19:47",
                                      "tag_id": 89
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                      },
                      {
                          "id": 20,
                          "name": "feature_importance_LinearModel",
                          "description": [
                              "所选特征列均为连续型/离散型数值，若为离散字符型，则先进行数据特征转换为数值型。",
                              "计算线性模型的特征重要性，包括线性回归和二分类逻辑回归。",
                              "在线性模型中，特征的重要性可以通过系数（coefficients）来衡量。",
                              "在多元线性回归、岭回归或lasso等线性模型中，在单位特征值增加一个单位时，对应的系数值表示因变量输出值的增加程度。",
                              "系数越大表示该特征对于预测结果的影响越大，其重要性也越高。用importances参数表示。"
                          ],
                          "create_ts": 1688564533,
                          "create_time": "2023-07-05 21:42:13",
                          "update_ts": 1688987987,
                          "update_time": "2023-07-10 19:19:47",
                          "label": "线性模型特征重要性",
                          "icon": "",
                          "category_id": 502,
                          "is_enable": true,
                          "operator": {
                              "id": 74,
                              "name": "feature_importance_LinearModel",
                              "description": [
                                  "所选特征列均为连续型/离散型数值，若为离散字符型，则先进行数据特征转换为数值型。",
                                  "计算线性模型的特征重要性，包括线性回归和二分类逻辑回归。",
                                  "在线性模型中，特征的重要性可以通过系数（coefficients）来衡量。",
                                  "在多元线性回归、岭回归或lasso等线性模型中，在单位特征值增加一个单位时，对应的系数值表示因变量输出值的增加程度。",
                                  "系数越大表示该特征对于预测结果的影响越大，其重要性也越高。用importances参数表示。"
                              ],
                              "create_ts": 1688987987,
                              "create_time": "2023-07-10 19:19:47",
                              "update_ts": 1688987987,
                              "update_time": "2023-07-10 19:19:47",
                              "input_num": 1,
                              "output_num": 2,
                              "icon": "",
                              "category_id": 502,
                              "doc_url": "docs/canvas_operator/feature_engineering/feature_importance_LinearModel",
                              "version": "1.0.1",
                              "is_enable": true,
                              "template_id": 20,
                              "package_label": "scikit-learn",
                              "function_label": "wai_feature_importance_LinearModel",
                              "run_function": "run",
                              "run_filepath": "main.py",
                              "language_name": "python",
                              "framework_name": null,
                              "stage_name": "开发",
                              "language_code": "python",
                              "framework_code": null,
                              "stage_code": "dev",
                              "inputs": [
                                  {
                                      "id": 139,
                                      "name": "inputTable",
                                      "description": [
                                          "数据"
                                      ],
                                      "sequence": 1,
                                      "value_type_code": "dataframe",
                                      "value_type_name": "数据帧",
                                      "label": "数据"
                                  }
                              ],
                              "outputs": [
                                  {
                                      "id": 140,
                                      "name": "index_result",
                                      "description": [
                                          "返回各变量对应指标值矩阵"
                                      ],
                                      "sequence": 1,
                                      "value_type_code": "dataframe",
                                      "value_type_name": "数据帧",
                                      "label": "各变量对应指标值"
                                  },
                                  {
                                      "id": 141,
                                      "name": "resultdata",
                                      "description": [
                                          "返回经过指标变量筛选的矩阵"
                                      ],
                                      "sequence": 2,
                                      "value_type_code": "dataframe",
                                      "value_type_name": "数据帧",
                                      "label": "生成矩阵"
                                  }
                              ],
                              "configs": {
                                  "default": {
                                      "label": "默认",
                                      "results": [
                                          {
                                              "label": "默认",
                                              "results": [
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                                                      "id": 166,
                                                      "name": "labelColName",
                                                      "description": "选择筛选的特征目标列。",
                                                      "sequence": 1,
                                                      "label": "选择目标列",
                                                      "default_value": null,
                                                      "value_type_code": "list",
                                                      "value_type_name": "列表",
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                                                      "ui_type_name": "dynamicParameter",
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                                                  {
                                                      "id": 167,
                                                      "name": "featureColNames",
                                                      "description": "选择待与目标列计算的相关特征列，无数量限制。",
                                                      "sequence": 2,
                                                      "label": "选择待与目标列计算的相关特征列",
                                                      "default_value": null,
                                                      "value_type_code": "list",
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                                                      "is_enable": true,
                                                      "ui_type_code": "dynamicParameter",
                                                      "ui_type_name": "dynamicParameter",
                                                      "ui_config": null,
                                                      "section_sequence": 0
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                                                  {
                                                      "id": 168,
                                                      "name": "chose_filter",
                                                      "description": [
                                                          "选择要进行条件筛选的特征列，通过<列>选择参数，通过<类型>选择条件，填写<值>选择所需对比的参数值（该值自定义填写），通过<运算符>选择多个条件之间的合并关系。"
                                                      ],
                                                      "sequence": 3,
                                                      "label": "依据条件筛选保留特征列",
                                                      "default_value": null,
                                                      "value_type_code": "list",
                                                      "value_type_name": "列表",
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                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "conditionScreen",
                                                      "ui_type_name": "conditionScreen",
                                                      "ui_config": null,
                                                      "section_sequence": 0
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                      },
                      {
                          "id": 21,
                          "name": "feature_importance_RandomForest",
                          "description": [
                              "通过随机森林模型探索不同的方法来解释特征的重要性。",
                              "对于随机森林模型，评估特征重要性的方法通常有三种：Entropy Gain、Gini Importance 和 Permutation Importance。其中，前两种是经典的特征选择算法，而 Permutation Importance 是一种基于排列变化的特征筛选技术。",
                              "EntropyGain，该方法通过衡量决策树中节点不确定性的减少程度（基于信息论中的信息熵值变化）来评估特征重要性。在理论上，该算法更加灵敏而且对输入数据的单位改变更加鲁棒，主要用于分类问题。",
                              "Gini Importance，通过比较不同特征划分后的纯度提升程度来衡量特征重要性，更关注分类准确性方面的问题。当一个特征的 Gini Importance 最大时，即为该特征最重要的特征之一。",
                              "Permutation Importance，此方法通过修改数据中某些特征的值来评估其影响，从而评估特征的重要性，适用于回归、分类等多种场景。变化的差异越大，说明该特征在算法的决策中越重要。"
                          ],
                          "create_ts": 1688564533,
                          "create_time": "2023-07-05 21:42:13",
                          "update_ts": 1688987987,
                          "update_time": "2023-07-10 19:19:47",
                          "label": "随机森林特征重要性",
                          "icon": "",
                          "category_id": 502,
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                          "operator": {
                              "id": 75,
                              "name": "feature_importance_RandomForest",
                              "description": [
                                  "通过随机森林模型探索不同的方法来解释特征的重要性。",
                                  "对于随机森林模型，评估特征重要性的方法通常有三种：Entropy Gain、Gini Importance 和 Permutation Importance。其中，前两种是经典的特征选择算法，而 Permutation Importance 是一种基于排列变化的特征筛选技术。",
                                  "EntropyGain，该方法通过衡量决策树中节点不确定性的减少程度（基于信息论中的信息熵值变化）来评估特征重要性。在理论上，该算法更加灵敏而且对输入数据的单位改变更加鲁棒，主要用于分类问题。",
                                  "Gini Importance，通过比较不同特征划分后的纯度提升程度来衡量特征重要性，更关注分类准确性方面的问题。当一个特征的 Gini Importance 最大时，即为该特征最重要的特征之一。",
                                  "Permutation Importance，此方法通过修改数据中某些特征的值来评估其影响，从而评估特征的重要性，适用于回归、分类等多种场景。变化的差异越大，说明该特征在算法的决策中越重要。"
                              ],
                              "create_ts": 1688987987,
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                              "update_ts": 1688987987,
                              "update_time": "2023-07-10 19:19:47",
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                              "output_num": 2,
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                              "category_id": 502,
                              "doc_url": "docs/canvas_operator/feature_engineering/feature_importance_RandomForest",
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                              "template_id": 21,
                              "package_label": "scikit-learn",
                              "function_label": "wai_feature_importance_LinearModel",
                              "run_function": "run",
                              "run_filepath": "main.py",
                              "language_name": "python",
                              "framework_name": null,
                              "stage_name": "开发",
                              "language_code": "python",
                              "framework_code": null,
                              "stage_code": "dev",
                              "inputs": [
                                  {
                                      "id": 142,
                                      "name": "inputTable",
                                      "description": [
                                          "数据"
                                      ],
                                      "sequence": 1,
                                      "value_type_code": "dataframe",
                                      "value_type_name": "数据帧",
                                      "label": "数据"
                                  }
                              ],
                              "outputs": [
                                  {
                                      "id": 143,
                                      "name": "index_result",
                                      "description": [
                                          "返回各变量对应指标值矩阵"
                                      ],
                                      "sequence": 1,
                                      "value_type_code": "dataframe",
                                      "value_type_name": "数据帧",
                                      "label": "各变量对应指标值"
                                  },
                                  {
                                      "id": 144,
                                      "name": "resultdata",
                                      "description": [
                                          "返回经过指标变量筛选的矩阵"
                                      ],
                                      "sequence": 2,
                                      "value_type_code": "dataframe",
                                      "value_type_name": "数据帧",
                                      "label": "生成矩阵"
                                  }
                              ],
                              "configs": {
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                                      "results": [
                                          {
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                                              "results": [
                                                  {
                                                      "id": 169,
                                                      "name": "labelColName",
                                                      "description": "选择筛选的特征标签列。",
                                                      "sequence": 1,
                                                      "label": "选择标签列",
                                                      "default_value": null,
                                                      "value_type_code": "list",
                                                      "value_type_name": "列表",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "dynamicParameter",
                                                      "ui_type_name": "dynamicParameter",
                                                      "ui_config": {
                                                          "limit_num": 1
                                                      },
                                                      "section_sequence": 0
                                                  },
                                                  {
                                                      "id": 170,
                                                      "name": "featureColNames",
                                                      "description": "选择相关特征列。",
                                                      "sequence": 2,
                                                      "label": "选择相关特征列",
                                                      "default_value": null,
                                                      "value_type_code": "list",
                                                      "value_type_name": "列表",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "dynamicParameter",
                                                      "ui_type_name": "dynamicParameter",
                                                      "ui_config": null,
                                                      "section_sequence": 0
                                                  },
                                                  {
                                                      "id": 171,
                                                      "name": "chose_filter",
                                                      "description": [
                                                          "选择要进行条件筛选的特征列，通过<列>选择参数，通过<类型>选择条件，填写<值>选择所需对比的参数值（该值自定义填写），通过<运算符>选择多个条件之间的合并关系。"
                                                      ],
                                                      "sequence": 3,
                                                      "label": "依据条件筛选保留特征列",
                                                      "default_value": null,
                                                      "value_type_code": "list",
                                                      "value_type_name": "列表",
                                                      "is_required": false,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "conditionScreen",
                                                      "ui_type_name": "conditionScreen",
                                                      "ui_config": null,
                                                      "section_sequence": 0
                                                  }
                                              ]
                                          }
                                      ]
                                  },
                                  "runtime": {
                                      "label": "运行期间",
                                      "results": []
                                  },
                                  "framework": {
                                      "label": "框架",
                                      "results": []
                                  },
                                  "section": {
                                      "label": "自定义",
                                      "results": []
                                  }
                              },
                              "tags": [
                                  {
                                      "id": 150,
                                      "tag_name": "特征重要性评估",
                                      "create_time": "2023-07-10 19:19:47",
                                      "tag_id": 89
                                  },
                                  {
                                      "id": 151,
                                      "tag_name": "随机森林特征重要性",
                                      "create_time": "2023-07-10 19:19:47",
                                      "tag_id": 91
                                  }
                              ],
                              "storages": {
                                  "artifact": false,
                                  "model": false,
                                  "data": false
                              },
                              "upstreams": {
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                                      "data_visualization",
                                      "statistical_analysis",
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                                  ],
                                  "only": null
                              },
                              "downstreams": {
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                                      "datasource",
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                                  "only": null
                              },
                              "category_name": "feature_importance",
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                          },
                          "sequence": 0,
                          "is_delete": false,
                          "delete_ts": null,
                          "delete_time": null,
                          "source_type_code": "official",
                          "source_type_name": "官方"
                      }
                  ],
                  "resources_total": 3
              }
          ],
          "resources": [],
          "resources_total": 10
      },
      {
          "id": 6,
          "name": "ml",
          "sequence": 6,
          "description": "机器学习",
          "create_ts": 1645515710,
          "create_time": "2022-02-22 15:41:50",
          "is_enable": true,
          "nodes": [
              {
                  "id": 601,
                  "name": "clustering",
                  "sequence": 1,
                  "description": "聚类",
                  "create_ts": 1645515710,
                  "create_time": "2022-02-22 15:41:50",
                  "is_enable": true,
                  "nodes": [],
                  "resources": [
                      {
                          "id": 32,
                          "name": "clustering_dbscan_model",
                          "description": [
                              "DBSCAN是一种基于密度的聚类算法，其核心思想是寻找高密度区域，并将这些高密度区域视为一个簇，同时使用一些特殊的技术可以排除噪声点。",
                              "相对于其他聚类算法，DBSCAN在处理非球形数据、噪声点以及不同密度数据方面具有优势。"
                          ],
                          "create_ts": 1688564534,
                          "create_time": "2023-07-05 21:42:14",
                          "update_ts": 1688987988,
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                          "label": "DBSCAN聚类模型",
                          "icon": "",
                          "category_id": 601,
                          "is_enable": true,
                          "operator": {
                              "id": 86,
                              "name": "clustering_dbscan_model",
                              "description": [
                                  "DBSCAN是一种基于密度的聚类算法，其核心思想是寻找高密度区域，并将这些高密度区域视为一个簇，同时使用一些特殊的技术可以排除噪声点。",
                                  "相对于其他聚类算法，DBSCAN在处理非球形数据、噪声点以及不同密度数据方面具有优势。"
                              ],
                              "create_ts": 1688987988,
                              "create_time": "2023-07-10 19:19:48",
                              "update_ts": 1688987988,
                              "update_time": "2023-07-10 19:19:48",
                              "input_num": 0,
                              "output_num": 1,
                              "icon": "",
                              "category_id": 601,
                              "doc_url": "docs/canvas_operator/machine_learning/clustering/clustering_dbscan_model",
                              "version": "1.0.1",
                              "is_enable": true,
                              "template_id": 32,
                              "package_label": "sklearn.cluster",
                              "function_label": "DBSCAN",
                              "run_function": "run",
                              "run_filepath": "main.py",
                              "language_name": "python",
                              "framework_name": null,
                              "stage_name": "开发",
                              "language_code": "python",
                              "framework_code": null,
                              "stage_code": "dev",
                              "inputs": [],
                              "outputs": [
                                  {
                                      "id": 167,
                                      "name": "model",
                                      "description": [
                                          "模型对象"
                                      ],
                                      "sequence": 1,
                                      "value_type_code": "model",
                                      "value_type_name": "model",
                                      "label": "模型对象"
                                  }
                              ],
                              "configs": {
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                                      "results": []
                                  },
                                  "runtime": {
                                      "label": "运行期间",
                                      "results": []
                                  },
                                  "framework": {
                                      "label": "框架",
                                      "results": []
                                  },
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                                      "label": "自定义",
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                                          {
                                              "label": "模型参数",
                                              "results": [
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                                                      "id": 203,
                                                      "name": "eps",
                                                      "description": "用于设置密度聚类中的ε领域，即半径，默认为0.5。",
                                                      "sequence": 1,
                                                      "label": "eps",
                                                      "default_value": "0.5",
                                                      "value_type_code": "float",
                                                      "value_type_name": "浮点数",
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                                                      "is_visible": true,
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                                                      "is_enable": true,
                                                      "ui_type_code": "inputNumber",
                                                      "ui_type_name": "inputNumber",
                                                      "ui_config": {
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                                                          "step": 0.01,
                                                          "precision": 2
                                                      },
                                                      "section_sequence": 1
                                                  },
                                                  {
                                                      "id": 204,
                                                      "name": "min_samples",
                                                      "description": "用于设置ε领域内最少的样本量，默认为5。",
                                                      "sequence": 2,
                                                      "label": "min_samples",
                                                      "default_value": "5",
                                                      "value_type_code": "int",
                                                      "value_type_name": "整型",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "inputNumber",
                                                      "ui_type_name": "inputNumber",
                                                      "ui_config": {
                                                          "min": 0,
                                                          "max": 999999,
                                                          "step": 1
                                                      },
                                                      "section_sequence": 1
                                                  }
                                              ]
                                          },
                                          {
                                              "label": "调优参数",
                                              "results": [
                                                  {
                                                      "id": 205,
                                                      "name": "algorithm",
                                                      "description": "在计算点之间距离的过程中，用于指定搜寻最近邻样本点的算法。默认为auto，表示密度聚类会自动选择一个合适的搜寻方法。如果为ball_tree，则表示使用球树搜寻最近邻。如果为kd_tree，则表示使用K-D树搜寻最近邻。如果为brute，则表示使用暴力法搜寻最近邻。",
                                                      "sequence": 1,
                                                      "label": "algorithm",
                                                      "default_value": null,
                                                      "value_type_code": "string",
                                                      "value_type_name": "字符串",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "radio",
                                                      "ui_type_name": "radio",
                                                      "ui_config": {
                                                          "options": [
                                                              {
                                                                  "label": "auto",
                                                                  "value": "auto"
                                                              },
                                                              {
                                                                  "label": "ball_tree",
                                                                  "value": "ball_tree"
                                                              },
                                                              {
                                                                  "label": "kd_tree",
                                                                  "value": "kd_tree"
                                                              },
                                                              {
                                                                  "label": "brute",
                                                                  "value": "brute"
                                                              }
                                                          ]
                                                      },
                                                      "section_sequence": 2
                                                  }
                                              ]
                                          }
                                      ]
                                  }
                              },
                              "tags": [
                                  {
                                      "id": 174,
                                      "tag_name": "DBSCAN",
                                      "create_time": "2023-07-10 19:19:48",
                                      "tag_id": 107
                                  },
                                  {
                                      "id": 175,
                                      "tag_name": "聚类",
                                      "create_time": "2023-07-10 19:19:48",
                                      "tag_id": 108
                                  }
                              ],
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                                  "data": false
                              },
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                                      "evaluate_model"
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                              },
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                              },
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                          },
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                          "delete_ts": null,
                          "delete_time": null,
                          "source_type_code": "official",
                          "source_type_name": "官方"
                      },
                      {
                          "id": 33,
                          "name": "clustering_gmm_model",
                          "description": [
                              "GaussianMixture是一种基于统计的聚类算法，用于描述多元数据分布情况。",
                              "基本思想是将所有数据视为由多维高斯分布组成的混合分布，并通过拟合这个混合分布来实现聚类。"
                          ],
                          "create_ts": 1688564534,
                          "create_time": "2023-07-05 21:42:14",
                          "update_ts": 1688987988,
                          "update_time": "2023-07-10 19:19:48",
                          "label": "GMM聚类模型",
                          "icon": "",
                          "category_id": 601,
                          "is_enable": true,
                          "operator": {
                              "id": 87,
                              "name": "clustering_gmm_model",
                              "description": [
                                  "GaussianMixture是一种基于统计的聚类算法，用于描述多元数据分布情况。",
                                  "基本思想是将所有数据视为由多维高斯分布组成的混合分布，并通过拟合这个混合分布来实现聚类。"
                              ],
                              "create_ts": 1688987988,
                              "create_time": "2023-07-10 19:19:48",
                              "update_ts": 1688987988,
                              "update_time": "2023-07-10 19:19:48",
                              "input_num": 0,
                              "output_num": 1,
                              "icon": "",
                              "category_id": 601,
                              "doc_url": "docs/canvas_operator/machine_learning/clustering/clustering_gmm_model",
                              "version": "1.0.1",
                              "is_enable": true,
                              "template_id": 33,
                              "package_label": "sklearn.mixture",
                              "function_label": "GaussianMixture",
                              "run_function": "run",
                              "run_filepath": "main.py",
                              "language_name": "python",
                              "framework_name": null,
                              "stage_name": "开发",
                              "language_code": "python",
                              "framework_code": null,
                              "stage_code": "dev",
                              "inputs": [],
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                                      "id": 168,
                                      "name": "model",
                                      "description": [
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                                      "value_type_code": "model",
                                      "value_type_name": "model",
                                      "label": "模型对象"
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                                      "results": []
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                                      "results": []
                                  },
                                  "framework": {
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                                      "results": []
                                  },
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                                              "label": "模型参数",
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                                                      "id": 206,
                                                      "name": "n_components",
                                                      "description": "混合高斯模型个数，默认为2。",
                                                      "sequence": 1,
                                                      "label": "n_components",
                                                      "default_value": "2",
                                                      "value_type_code": "int",
                                                      "value_type_name": "整型",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "inputNumber",
                                                      "ui_type_name": "inputNumber",
                                                      "ui_config": {
                                                          "min": 2,
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                                                      },
                                                      "section_sequence": 1
                                                  },
                                                  {
                                                      "id": 207,
                                                      "name": "covariance_type",
                                                      "description": "协方差类型，协方差类型。full指每个分量有各自不同的标准协方差矩阵；tied指所有分量有相同的标准协方差矩阵；diag指每个分量有各自不同对角协方差矩阵；spherical指每个分量有各自不同的简单协方差矩阵，球面协方差矩阵。",
                                                      "sequence": 2,
                                                      "label": "covariance_type",
                                                      "default_value": "full",
                                                      "value_type_code": "string",
                                                      "value_type_name": "字符串",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "radio",
                                                      "ui_type_name": "radio",
                                                      "ui_config": {
                                                          "options": [
                                                              {
                                                                  "label": "full",
                                                                  "value": "full"
                                                              },
                                                              {
                                                                  "label": "tied",
                                                                  "value": "tied"
                                                              },
                                                              {
                                                                  "label": "diag",
                                                                  "value": "diag"
                                                              },
                                                              {
                                                                  "label": "spherical",
                                                                  "value": "spherical"
                                                              }
                                                          ]
                                                      },
                                                      "section_sequence": 1
                                                  }
                                              ]
                                          },
                                          {
                                              "label": "调优参数",
                                              "results": [
                                                  {
                                                      "id": 208,
                                                      "name": "tol",
                                                      "description": "EM迭代停止阈值，默认为1e-3，即0.001。",
                                                      "sequence": 1,
                                                      "label": "tol",
                                                      "default_value": "0.001",
                                                      "value_type_code": "float",
                                                      "value_type_name": "浮点数",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "inputNumber",
                                                      "ui_type_name": "inputNumber",
                                                      "ui_config": {
                                                          "min": 0,
                                                          "max": 999999,
                                                          "step": 0.001
                                                      },
                                                      "section_sequence": 2
                                                  },
                                                  {
                                                      "id": 209,
                                                      "name": "max_iter",
                                                      "description": "最大迭代次数，默认100。",
                                                      "sequence": 2,
                                                      "label": "max_iter",
                                                      "default_value": "100",
                                                      "value_type_code": "int",
                                                      "value_type_name": "整型",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "inputNumber",
                                                      "ui_type_name": "inputNumber",
                                                      "ui_config": {
                                                          "min": 0,
                                                          "max": 999999,
                                                          "step": 1
                                                      },
                                                      "section_sequence": 2
                                                  },
                                                  {
                                                      "id": 210,
                                                      "name": "n_init",
                                                      "description": "初始化次数，用于产生最佳初始参数，默认为1。",
                                                      "sequence": 3,
                                                      "label": "n_init",
                                                      "default_value": "1",
                                                      "value_type_code": "int",
                                                      "value_type_name": "整型",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "inputNumber",
                                                      "ui_type_name": "inputNumber",
                                                      "ui_config": {
                                                          "min": 0,
                                                          "max": 999999,
                                                          "step": 1
                                                      },
                                                      "section_sequence": 2
                                                  },
                                                  {
                                                      "id": 211,
                                                      "name": "init_params",
                                                      "description": "初始化参数类型{kmeans, random}，初始化参数实现方式，默认用kmeans实现，也可以选择随机产生。",
                                                      "sequence": 4,
                                                      "label": "init_params",
                                                      "default_value": "kmeans",
                                                      "value_type_code": "string",
                                                      "value_type_name": "字符串",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "radio",
                                                      "ui_type_name": "radio",
                                                      "ui_config": {
                                                          "options": [
                                                              {
                                                                  "label": "kmeans",
                                                                  "value": "kmeans"
                                                              },
                                                              {
                                                                  "label": "random",
                                                                  "value": "random"
                                                              }
                                                          ]
                                                      },
                                                      "section_sequence": 2
                                                  }
                                              ]
                                          }
                                      ]
                                  }
                              },
                              "tags": [
                                  {
                                      "id": 177,
                                      "tag_name": "聚类",
                                      "create_time": "2023-07-10 19:19:48",
                                      "tag_id": 108
                                  },
                                  {
                                      "id": 176,
                                      "tag_name": "GMM",
                                      "create_time": "2023-07-10 19:19:48",
                                      "tag_id": 109
                                  }
                              ],
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                                  "model": false,
                                  "data": false
                              },
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                              },
                              "downstreams": {
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                              },
                              "category_name": "clustering",
                              "label": "GMM聚类模型"
                          },
                          "sequence": 0,
                          "is_delete": false,
                          "delete_ts": null,
                          "delete_time": null,
                          "source_type_code": "official",
                          "source_type_name": "官方"
                      },
                      {
                          "id": 34,
                          "name": "clustering_kmeans_model",
                          "description": [
                              "KMeans 是一种基于距离的聚类算法，将数据点划分到k个不同的簇中，使得每个数据点都属于离其最近的某个簇。",
                              "核心思想就是通过将所有数据点归属到k个簇中，让每个簇内部数据点的相似度达到最大化，并让不同簇之间的差异度达到最小化。"
                          ],
                          "create_ts": 1688564534,
                          "create_time": "2023-07-05 21:42:14",
                          "update_ts": 1688987988,
                          "update_time": "2023-07-10 19:19:48",
                          "label": "K-means聚类模型",
                          "icon": "",
                          "category_id": 601,
                          "is_enable": true,
                          "operator": {
                              "id": 88,
                              "name": "clustering_kmeans_model",
                              "description": [
                                  "KMeans 是一种基于距离的聚类算法，将数据点划分到k个不同的簇中，使得每个数据点都属于离其最近的某个簇。",
                                  "核心思想就是通过将所有数据点归属到k个簇中，让每个簇内部数据点的相似度达到最大化，并让不同簇之间的差异度达到最小化。"
                              ],
                              "create_ts": 1688987988,
                              "create_time": "2023-07-10 19:19:48",
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                              "在训练前，我们需要设置好相应的超参数并标准化特征数据。"
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                                  "基础思想为拟合数据，并得到一个线性方程，从而预测实际数值Y和自变量X之间的关系。"
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                                                      "description": "默认True，否则X会被改写。",
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                                                      "default_value": "True",
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                                                      "id": 265,
                                                      "name": "n_estimators",
                                                      "description": "提升树的数量，即训练轮数。",
                                                      "sequence": 1,
                                                      "label": "n_estimators",
                                                      "default_value": "100",
                                                      "value_type_code": "int",
                                                      "value_type_name": "整型",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "inputNumber",
                                                      "ui_type_name": "inputNumber",
                                                      "ui_config": {
                                                          "min": 0,
                                                          "max": 9999,
                                                          "step": 1
                                                      },
                                                      "section_sequence": 1
                                                  },
                                                  {
                                                      "id": 266,
                                                      "name": "max_depth",
                                                      "description": "树的最大深度。",
                                                      "sequence": 2,
                                                      "label": "max_depth",
                                                      "default_value": "30",
                                                      "value_type_code": "int",
                                                      "value_type_name": "整型",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "inputNumber",
                                                      "ui_type_name": "inputNumber",
                                                      "ui_config": {
                                                          "min": 0,
                                                          "max": 9999,
                                                          "step": 1
                                                      },
                                                      "section_sequence": 1
                                                  },
                                                  {
                                                      "id": 267,
                                                      "name": "learning_rate",
                                                      "description": "学习率。",
                                                      "sequence": 3,
                                                      "label": "learning_rate",
                                                      "default_value": "0.01",
                                                      "value_type_code": "float",
                                                      "value_type_name": "浮点数",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "inputNumber",
                                                      "ui_type_name": "inputNumber",
                                                      "ui_config": {
                                                          "min": 0,
                                                          "max": 99,
                                                          "step": 0.001
                                                      },
                                                      "section_sequence": 1
                                                  }
                                              ]
                                          },
                                          {
                                              "label": "调优参数",
                                              "results": [
                                                  {
                                                      "id": 268,
                                                      "name": "objective",
                                                      "description": "学习目标及其损失函数。",
                                                      "sequence": 1,
                                                      "label": "objective",
                                                      "default_value": "reg:squaredlogerror",
                                                      "value_type_code": "string",
                                                      "value_type_name": "字符串",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "radio",
                                                      "ui_type_name": "radio",
                                                      "ui_config": {
                                                          "options": [
                                                              {
                                                                  "label": "reg:squaredlogerror",
                                                                  "value": "reg:squaredlogerror"
                                                              },
                                                              {
                                                                  "label": "reg:logistic",
                                                                  "value": "reg:logistic"
                                                              }
                                                          ]
                                                      },
                                                      "section_sequence": 2
                                                  },
                                                  {
                                                      "id": 269,
                                                      "name": "booster",
                                                      "description": "弱评估器。",
                                                      "sequence": 2,
                                                      "label": "booster",
                                                      "default_value": "gbtree",
                                                      "value_type_code": "string",
                                                      "value_type_name": "字符串",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "radio",
                                                      "ui_type_name": "radio",
                                                      "ui_config": {
                                                          "options": [
                                                              {
                                                                  "label": "gbtree",
                                                                  "value": "gbtree"
                                                              },
                                                              {
                                                                  "label": "gblinear",
                                                                  "value": "gblinear"
                                                              },
                                                              {
                                                                  "label": "dart",
                                                                  "value": "dart"
                                                              }
                                                          ]
                                                      },
                                                      "section_sequence": 2
                                                  },
                                                  {
                                                      "id": 270,
                                                      "name": "importance_type",
                                                      "description": "计算特征重要性的依据。",
                                                      "sequence": 3,
                                                      "label": "importance_type",
                                                      "default_value": "gain",
                                                      "value_type_code": "string",
                                                      "value_type_name": "字符串",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "radio",
                                                      "ui_type_name": "radio",
                                                      "ui_config": {
                                                          "options": [
                                                              {
                                                                  "label": "gain",
                                                                  "value": "gain"
                                                              },
                                                              {
                                                                  "label": "weight",
                                                                  "value": "weight"
                                                              },
                                                              {
                                                                  "label": "cover",
                                                                  "value": "cover"
                                                              },
                                                              {
                                                                  "label": "total_gain",
                                                                  "value": "total_gain"
                                                              },
                                                              {
                                                                  "label": "total_cover",
                                                                  "value": "total_cover"
                                                              }
                                                          ]
                                                      },
                                                      "section_sequence": 2
                                                  },
                                                  {
                                                      "id": 271,
                                                      "name": "tree_method",
                                                      "description": "构建树采用的算法。",
                                                      "sequence": 4,
                                                      "label": "tree_method",
                                                      "default_value": "auto",
                                                      "value_type_code": "string",
                                                      "value_type_name": "字符串",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "radio",
                                                      "ui_type_name": "radio",
                                                      "ui_config": {
                                                          "options": [
                                                              {
                                                                  "label": "auto",
                                                                  "value": "auto"
                                                              },
                                                              {
                                                                  "label": "exact",
                                                                  "value": "exact"
                                                              },
                                                              {
                                                                  "label": "approx",
                                                                  "value": "approx"
                                                              },
                                                              {
                                                                  "label": "hist",
                                                                  "value": "hist"
                                                              },
                                                              {
                                                                  "label": "gpu_hist",
                                                                  "value": "gpu_hist"
                                                              }
                                                          ]
                                                      },
                                                      "section_sequence": 2
                                                  }
                                              ]
                                          }
                                      ]
                                  }
                              },
                              "tags": [
                                  {
                                      "id": 198,
                                      "tag_name": "回归",
                                      "create_time": "2023-07-10 19:19:50",
                                      "tag_id": 118
                                  },
                                  {
                                      "id": 197,
                                      "tag_name": "XGBoost回归模型",
                                      "create_time": "2023-07-10 19:19:50",
                                      "tag_id": 121
                                  }
                              ],
                              "storages": {
                                  "artifact": false,
                                  "model": false,
                                  "data": false
                              },
                              "upstreams": {
                                  "except": [
                                      "data_visualization",
                                      "evaluate_model"
                                  ],
                                  "only": null
                              },
                              "downstreams": {
                                  "except": [
                                      "datasource"
                                  ],
                                  "only": null
                              },
                              "category_name": "regression",
                              "label": "XGBoost回归模型"
                          },
                          "sequence": 0,
                          "is_delete": false,
                          "delete_ts": null,
                          "delete_time": null,
                          "source_type_code": "official",
                          "source_type_name": "官方"
                      }
                  ],
                  "resources_total": 5
              },
              {
                  "id": 603,
                  "name": "binary_classification",
                  "sequence": 3,
                  "description": "二分类",
                  "create_ts": 1645515710,
                  "create_time": "2022-02-22 15:41:50",
                  "is_enable": true,
                  "nodes": [],
                  "resources": [
                      {
                          "id": 29,
                          "name": "bc_GBDT_model",
                          "description": [
                              "GBDT（Gradient Boosting Decision Tree）是一种基于决策树的梯度提升算法，主要用于二分类或多分类问题。",
                              "通过进行集合预测累加，不断调整误差来提高模型预测性能。",
                              "在GBDT训练过程中，每一轮迭代都会在当前模型已有的基础上产生一个新的决策树模型，并且该新模型的输出会被当前模型输出累加，从而减小数据的残差误差，达到提高模型性能的目的。"
                          ],
                          "create_ts": 1688564534,
                          "create_time": "2023-07-05 21:42:14",
                          "update_ts": 1688987988,
                          "update_time": "2023-07-10 19:19:48",
                          "label": "GBDT二分类模型",
                          "icon": "",
                          "category_id": 603,
                          "is_enable": true,
                          "operator": {
                              "id": 83,
                              "name": "bc_GBDT_model",
                              "description": [
                                  "GBDT（Gradient Boosting Decision Tree）是一种基于决策树的梯度提升算法，主要用于二分类或多分类问题。",
                                  "通过进行集合预测累加，不断调整误差来提高模型预测性能。",
                                  "在GBDT训练过程中，每一轮迭代都会在当前模型已有的基础上产生一个新的决策树模型，并且该新模型的输出会被当前模型输出累加，从而减小数据的残差误差，达到提高模型性能的目的。"
                              ],
                              "create_ts": 1688987988,
                              "create_time": "2023-07-10 19:19:48",
                              "update_ts": 1688987988,
                              "update_time": "2023-07-10 19:19:48",
                              "input_num": 0,
                              "output_num": 1,
                              "icon": "",
                              "category_id": 603,
                              "doc_url": "docs/canvas_operator/machine_learning/binary_classification/binary_classification_GBDT_model",
                              "version": "1.0.1",
                              "is_enable": true,
                              "template_id": 29,
                              "package_label": "sklearn.ensemble",
                              "function_label": "GradientBoostingClassifier",
                              "run_function": "run",
                              "run_filepath": "main.py",
                              "language_name": "python",
                              "framework_name": null,
                              "stage_name": "开发",
                              "language_code": "python",
                              "framework_code": null,
                              "stage_code": "dev",
                              "inputs": [],
                              "outputs": [
                                  {
                                      "id": 164,
                                      "name": "model",
                                      "description": [
                                          "模型对象"
                                      ],
                                      "sequence": 1,
                                      "value_type_code": "model",
                                      "value_type_name": "model",
                                      "label": "模型对象"
                                  }
                              ],
                              "configs": {
                                  "default": {
                                      "label": "默认",
                                      "results": []
                                  },
                                  "runtime": {
                                      "label": "运行期间",
                                      "results": []
                                  },
                                  "framework": {
                                      "label": "框架",
                                      "results": []
                                  },
                                  "section": {
                                      "label": "自定义",
                                      "results": [
                                          {
                                              "label": "模型参数",
                                              "results": [
                                                  {
                                                      "id": 178,
                                                      "name": "loss",
                                                      "description": "deviance是采用对数似然，exponential是指数损失，后者相当于AdaBoost。",
                                                      "sequence": 1,
                                                      "label": "loss",
                                                      "default_value": null,
                                                      "value_type_code": "string",
                                                      "value_type_name": "字符串",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "radio",
                                                      "ui_type_name": "radio",
                                                      "ui_config": {
                                                          "options": [
                                                              {
                                                                  "label": "deviance",
                                                                  "value": "deviance"
                                                              },
                                                              {
                                                                  "label": "exponential",
                                                                  "value": "exponential"
                                                              }
                                                          ]
                                                      },
                                                      "section_sequence": 1
                                                  },
                                                  {
                                                      "id": 179,
                                                      "name": "n_estimators",
                                                      "description": "调参时要注意过拟合或欠拟合，一般和learning_rate一起考虑。",
                                                      "sequence": 2,
                                                      "label": "n_estimators",
                                                      "default_value": "100",
                                                      "value_type_code": "int",
                                                      "value_type_name": "整型",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "inputNumber",
                                                      "ui_type_name": "inputNumber",
                                                      "ui_config": {
                                                          "min": 0,
                                                          "max": 999999,
                                                          "step": 1
                                                      },
                                                      "section_sequence": 1
                                                  },
                                                  {
                                                      "id": 180,
                                                      "name": "learning_rate",
                                                      "description": "每个弱学习器的权重缩减系数，取值范围0-1，当取值为1时，相当于权重不缩减。较小的learning_rate相当于更多的迭代次数。",
                                                      "sequence": 3,
                                                      "label": "learning_rate",
                                                      "default_value": "0.1",
                                                      "value_type_code": "float",
                                                      "value_type_name": "浮点数",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "inputNumber",
                                                      "ui_type_name": "inputNumber",
                                                      "ui_config": {
                                                          "min": 0,
                                                          "max": 1,
                                                          "step": 1e-05
                                                      },
                                                      "section_sequence": 1
                                                  },
                                                  {
                                                      "id": 181,
                                                      "name": "subsample",
                                                      "description": "取值范围(0,1]，当取值为1时，相当于没有采样。小于1时，即进行采样，按比例采样得到的样本去构建弱学习器。这样做可以防止过拟合，但是值不能太低，会造成高方差。",
                                                      "sequence": 4,
                                                      "label": "subsample",
                                                      "default_value": "1",
                                                      "value_type_code": "float",
                                                      "value_type_name": "浮点数",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "inputNumber",
                                                      "ui_type_name": "inputNumber",
                                                      "ui_config": {
                                                          "min": 0,
                                                          "max": 1,
                                                          "step": 0.01
                                                      },
                                                      "section_sequence": 1
                                                  }
                                              ]
                                          },
                                          {
                                              "label": "调优参数",
                                              "results": [
                                                  {
                                                      "id": 182,
                                                      "name": "max_features",
                                                      "description": "默认为None，也就是考虑所有特征。可以取值有：log2,auto,sqrt。",
                                                      "sequence": 1,
                                                      "label": "max_features",
                                                      "default_value": null,
                                                      "value_type_code": "string",
                                                      "value_type_name": "字符串",
                                                      "is_required": false,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "radio",
                                                      "ui_type_name": "radio",
                                                      "ui_config": {
                                                          "options": [
                                                              {
                                                                  "label": "log2",
                                                                  "value": "log2"
                                                              },
                                                              {
                                                                  "label": "auto",
                                                                  "value": "auto"
                                                              },
                                                              {
                                                                  "label": "sqrt",
                                                                  "value": "sqrt"
                                                              }
                                                          ]
                                                      },
                                                      "section_sequence": 2
                                                  },
                                                  {
                                                      "id": 183,
                                                      "name": "max_depth",
                                                      "description": "CART最大深度。",
                                                      "sequence": 2,
                                                      "label": "max_depth",
                                                      "default_value": "10",
                                                      "value_type_code": "int",
                                                      "value_type_name": "整型",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "inputNumber",
                                                      "ui_type_name": "inputNumber",
                                                      "ui_config": {
                                                          "min": 0,
                                                          "max": 999999,
                                                          "step": 1
                                                      },
                                                      "section_sequence": 2
                                                  },
                                                  {
                                                      "id": 184,
                                                      "name": "min_samples_split",
                                                      "description": "当某节点的样本数小于某个值时，就当做叶子节点，不允许再分裂。默认是2。",
                                                      "sequence": 3,
                                                      "label": "min_samples_split",
                                                      "default_value": "2",
                                                      "value_type_code": "int",
                                                      "value_type_name": "整型",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "inputNumber",
                                                      "ui_type_name": "inputNumber",
                                                      "ui_config": {
                                                          "min": 0,
                                                          "max": 999999,
                                                          "step": 1
                                                      },
                                                      "section_sequence": 2
                                                  },
                                                  {
                                                      "id": 185,
                                                      "name": "min_samples_leaf",
                                                      "description": "如果某个叶子节点数量少于某个值，会同它的兄弟节点一起被剪枝。默认是1。",
                                                      "sequence": 4,
                                                      "label": "min_samples_leaf",
                                                      "default_value": "1",
                                                      "value_type_code": "int",
                                                      "value_type_name": "整型",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "inputNumber",
                                                      "ui_type_name": "inputNumber",
                                                      "ui_config": {
                                                          "min": 0,
                                                          "max": 999999,
                                                          "step": 1
                                                      },
                                                      "section_sequence": 2
                                                  },
                                                  {
                                                      "id": 186,
                                                      "name": "min_weight_fraction_leaf",
                                                      "description": "如果小于某个值，会同它的兄弟节点一起被剪枝。一般用于权重变化的样本。默认是0。",
                                                      "sequence": 5,
                                                      "label": "min_weight_fraction_leaf",
                                                      "default_value": "0",
                                                      "value_type_code": "float",
                                                      "value_type_name": "浮点数",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "inputNumber",
                                                      "ui_type_name": "inputNumber",
                                                      "ui_config": {
                                                          "min": 0,
                                                          "max": 999999,
                                                          "step": 0.01
                                                      },
                                                      "section_sequence": 2
                                                  }
                                              ]
                                          }
                                      ]
                                  }
                              },
                              "tags": [
                                  {
                                      "id": 168,
                                      "tag_name": "GBDT二分类",
                                      "create_time": "2023-07-10 19:19:48",
                                      "tag_id": 102
                                  },
                                  {
                                      "id": 169,
                                      "tag_name": "二分类",
                                      "create_time": "2023-07-10 19:19:48",
                                      "tag_id": 103
                                  }
                              ],
                              "storages": {
                                  "artifact": false,
                                  "model": false,
                                  "data": false
                              },
                              "upstreams": {
                                  "except": [
                                      "data_visualization",
                                      "evaluate_model"
                                  ],
                                  "only": null
                              },
                              "downstreams": {
                                  "except": [
                                      "datasource"
                                  ],
                                  "only": null
                              },
                              "category_name": "binary_classification",
                              "label": "GBDT二分类模型"
                          },
                          "sequence": 0,
                          "is_delete": false,
                          "delete_ts": null,
                          "delete_time": null,
                          "source_type_code": "official",
                          "source_type_name": "官方"
                      },
                      {
                          "id": 30,
                          "name": "binary_classification_logistic_regression_model",
                          "description": [
                              "LogisticRegression是一种经典的二分类算法，主要用于处理具有两个可能结果的问题，例如预测某个用户是否会购买一件商品、肿瘤的良性或恶性等问题。",
                              "使用确定性迭代最小化正则化的负似然函数作为损失函数，基于梯度下降算法来训练模型。"
                          ],
                          "create_ts": 1688564534,
                          "create_time": "2023-07-05 21:42:14",
                          "update_ts": 1688987988,
                          "update_time": "2023-07-10 19:19:48",
                          "label": "逻辑回归二分类模型",
                          "icon": "",
                          "category_id": 603,
                          "is_enable": true,
                          "operator": {
                              "id": 84,
                              "name": "binary_classification_logistic_regression_model",
                              "description": [
                                  "LogisticRegression是一种经典的二分类算法，主要用于处理具有两个可能结果的问题，例如预测某个用户是否会购买一件商品、肿瘤的良性或恶性等问题。",
                                  "使用确定性迭代最小化正则化的负似然函数作为损失函数，基于梯度下降算法来训练模型。"
                              ],
                              "create_ts": 1688987988,
                              "create_time": "2023-07-10 19:19:48",
                              "update_ts": 1688987988,
                              "update_time": "2023-07-10 19:19:48",
                              "input_num": 0,
                              "output_num": 1,
                              "icon": "",
                              "category_id": 603,
                              "doc_url": "docs/canvas_operator/machine_learning/binary_classification/binary_classification_logistic_regression_model",
                              "version": "1.0.1",
                              "is_enable": true,
                              "template_id": 30,
                              "package_label": "sklearn.linear_model",
                              "function_label": "LogisticRegression",
                              "run_function": "run",
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                              "framework_name": null,
                              "stage_name": "开发",
                              "language_code": "python",
                              "framework_code": null,
                              "stage_code": "dev",
                              "inputs": [],
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                                      "name": "model",
                                      "description": [
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                                      "value_type_code": "model",
                                      "value_type_name": "model",
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                              ],
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                                      "results": []
                                  },
                                  "runtime": {
                                      "label": "运行期间",
                                      "results": []
                                  },
                                  "framework": {
                                      "label": "框架",
                                      "results": []
                                  },
                                  "section": {
                                      "label": "自定义",
                                      "results": [
                                          {
                                              "label": "模型参数",
                                              "results": [
                                                  {
                                                      "id": 187,
                                                      "name": "penalty",
                                                      "description": "nettoncg, sag, lbfgs’只支持l2。l1正则化的损失函数不是连续可导的，而nettoncg, sag, lbfgs这三种算法需要损失函数的一阶或二阶连续可导。",
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                                                      "value_type_code": "string",
                                                      "value_type_name": "字符串",
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                                                      "ui_type_code": "radio",
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                                                                  "value": "l2"
                                                              }
                                                          ]
                                                      },
                                                      "section_sequence": 1
                                                  },
                                                  {
                                                      "id": 188,
                                                      "name": "tol",
                                                      "description": "优化算法停止的条件。当迭代前后的函数差值小于等于tol时就停止。",
                                                      "sequence": 2,
                                                      "label": "tol",
                                                      "default_value": "0.0001",
                                                      "value_type_code": "float",
                                                      "value_type_name": "浮点数",
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                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
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                                                      "section_sequence": 1
                                                  },
                                                  {
                                                      "id": 189,
                                                      "name": "C",
                                                      "description": "值越小，正则化越强。",
                                                      "sequence": 3,
                                                      "label": "C",
                                                      "default_value": "1",
                                                      "value_type_code": "float",
                                                      "value_type_name": "浮点数",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "slider",
                                                      "ui_type_name": "slider",
                                                      "ui_config": {
                                                          "min": 0,
                                                          "max": 1,
                                                          "step": 0.001,
                                                          "unitText": "系数值"
                                                      },
                                                      "section_sequence": 1
                                                  },
                                                  {
                                                      "id": 190,
                                                      "name": "fit_intercept",
                                                      "description": "选择逻辑回归模型中是否会有常数项b。",
                                                      "sequence": 4,
                                                      "label": "fit_intercept",
                                                      "default_value": null,
                                                      "value_type_code": "string",
                                                      "value_type_name": "字符串",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "radio",
                                                      "ui_type_name": "radio",
                                                      "ui_config": {
                                                          "options": [
                                                              {
                                                                  "label": "是",
                                                                  "value": "True"
                                                              },
                                                              {
                                                                  "label": "否",
                                                                  "value": "False"
                                                              }
                                                          ]
                                                      },
                                                      "section_sequence": 1
                                                  }
                                              ]
                                          },
                                          {
                                              "label": "调优参数",
                                              "results": [
                                                  {
                                                      "id": 191,
                                                      "name": "class_weight",
                                                      "description": "balanced,类库根据训练样本量来计算权重。某种类型的样本量越多，则权重越低。",
                                                      "sequence": 1,
                                                      "label": "class_weight",
                                                      "default_value": null,
                                                      "value_type_code": "string",
                                                      "value_type_name": "字符串",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "radio",
                                                      "ui_type_name": "radio",
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                                                                  "value": "balanced"
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                                                          "custom": true
                                                      },
                                                      "section_sequence": 2
                                                  },
                                                  {
                                                      "id": 192,
                                                      "name": "solver",
                                                      "description": "liblinear,使用坐标轴下降法来迭代优化损失函数。只支持OvR。lbfgs,拟牛顿法的一种。利用损失函数二阶导数矩阵即海森矩阵来迭代优化损失函数。newtoncg,牛顿法的一种。sag,随机平均梯度下降。每次迭代仅仅用一部分的样本来计算梯度，适合于样本数据多的时候。",
                                                      "sequence": 2,
                                                      "label": "solver",
                                                      "default_value": null,
                                                      "value_type_code": "string",
                                                      "value_type_name": "字符串",
                                                      "is_required": true,
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                                                      "is_enable": true,
                                                      "ui_type_code": "radio",
                                                      "ui_type_name": "radio",
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                                                                  "value": "lbfgs"
                                                              },
                                                              {
                                                                  "label": "newton-cg",
                                                                  "value": "newton-cg"
                                                              },
                                                              {
                                                                  "label": "sag",
                                                                  "value": "sag"
                                                              }
                                                          ]
                                                      },
                                                      "section_sequence": 2
                                                  },
                                                  {
                                                      "id": 193,
                                                      "name": "max_iter",
                                                      "description": "优化算法的迭代次数。",
                                                      "sequence": 3,
                                                      "label": "max_iter",
                                                      "default_value": "100",
                                                      "value_type_code": "int",
                                                      "value_type_name": "整型",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "inputNumber",
                                                      "ui_type_name": "inputNumber",
                                                      "ui_config": {
                                                          "min": 1,
                                                          "max": 999999,
                                                          "step": 1
                                                      },
                                                      "section_sequence": 2
                                                  },
                                                  {
                                                      "id": 194,
                                                      "name": "multi_class",
                                                      "description": "multinomial即为MvM。若是二元逻辑回归，二者区别不大。",
                                                      "sequence": 4,
                                                      "label": "multi_class",
                                                      "default_value": null,
                                                      "value_type_code": "string",
                                                      "value_type_name": "字符串",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "radio",
                                                      "ui_type_name": "radio",
                                                      "ui_config": {
                                                          "options": [
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                                                                  "label": "ovr",
                                                                  "value": "ovr"
                                                              },
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                                                                  "label": "multinomial",
                                                                  "value": "multinomial"
                                                              }
                                                          ]
                                                      },
                                                      "section_sequence": 2
                                                  }
                                              ]
                                          }
                                      ]
                                  }
                              },
                              "tags": [
                                  {
                                      "id": 171,
                                      "tag_name": "二分类",
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                                      "tag_id": 103
                                  },
                                  {
                                      "id": 170,
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                                  "model": false,
                                  "data": false
                              },
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                              },
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                              },
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                          "delete_time": null,
                          "source_type_code": "official",
                          "source_type_name": "官方"
                      },
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                          "id": 31,
                          "name": "binary_classification_svm_model",
                          "description": [
                              "SVC（支持向量分类器）算法是一种基于最大边界（maximum margin）的分类方法。",
                              "核心思想是在特征空间中找到一个能够完美分隔两个类别的超平面（Hyperplane），并且使得该超平面距离训练数据点的间隔最大化，以避免过拟合。"
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                          "update_ts": 1688987988,
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                          "label": "SVM二分类模型",
                          "icon": "",
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                          "operator": {
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                              "name": "binary_classification_svm_model",
                              "description": [
                                  "SVC（支持向量分类器）算法是一种基于最大边界（maximum margin）的分类方法。",
                                  "核心思想是在特征空间中找到一个能够完美分隔两个类别的超平面（Hyperplane），并且使得该超平面距离训练数据点的间隔最大化，以避免过拟合。"
                              ],
                              "create_ts": 1688987988,
                              "create_time": "2023-07-10 19:19:48",
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                              "stage_name": "开发",
                              "language_code": "python",
                              "framework_code": null,
                              "stage_code": "dev",
                              "inputs": [],
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                                      "id": 166,
                                      "name": "model",
                                      "description": [
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                                      ],
                                      "sequence": 1,
                                      "value_type_code": "model",
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                                      "label": "运行期间",
                                      "results": []
                                  },
                                  "framework": {
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                                      "results": []
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                                              "label": "模型参数",
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                                                      "id": 195,
                                                      "name": "C",
                                                      "description": "C越大，相当于惩罚松弛变量，松弛变量接近0，即对误分类的惩罚增大，趋向于对训练集全分对的情况，准确率很高，泛化能力弱。",
                                                      "sequence": 1,
                                                      "label": "C",
                                                      "default_value": "1",
                                                      "value_type_code": "float",
                                                      "value_type_name": "浮点数",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "slider",
                                                      "ui_type_name": "slider",
                                                      "ui_config": {
                                                          "min": 0.01,
                                                          "max": 999999,
                                                          "step": 0.01
                                                      },
                                                      "section_sequence": 1
                                                  },
                                                  {
                                                      "id": 196,
                                                      "name": "kernel",
                                                      "description": "包括线性，多项式，RBF函数，sigmoid。",
                                                      "sequence": 2,
                                                      "label": "kernel",
                                                      "default_value": "linear",
                                                      "value_type_code": "string",
                                                      "value_type_name": "字符串",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "radio",
                                                      "ui_type_name": "radio",
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                                                          "options": [
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                                                                  "label": "linear",
                                                                  "value": "linear"
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                                                              {
                                                                  "label": "poly",
                                                                  "value": "poly"
                                                              },
                                                              {
                                                                  "label": "rbf",
                                                                  "value": "rbf"
                                                              },
                                                              {
                                                                  "label": "sigmoid",
                                                                  "value": "sigmoid"
                                                              },
                                                              {
                                                                  "label": "precomputed",
                                                                  "value": "precomputed"
                                                              }
                                                          ]
                                                      },
                                                      "section_sequence": 1
                                                  }
                                              ]
                                          },
                                          {
                                              "label": "调优参数",
                                              "results": [
                                                  {
                                                      "id": 197,
                                                      "name": "gamma",
                                                      "description": "包括rbf，poly，sigmoid，auto。",
                                                      "sequence": 1,
                                                      "label": "gamma",
                                                      "default_value": "auto",
                                                      "value_type_code": "string",
                                                      "value_type_name": "字符串",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "radio",
                                                      "ui_type_name": "radio",
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                                                                  "label": "rbf",
                                                                  "value": "rbf"
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                                                              {
                                                                  "label": "poly",
                                                                  "value": "poly"
                                                              },
                                                              {
                                                                  "label": "sigmoid",
                                                                  "value": "sigmoid"
                                                              },
                                                              {
                                                                  "label": "auto",
                                                                  "value": "auto"
                                                              }
                                                          ]
                                                      },
                                                      "section_sequence": 2
                                                  },
                                                  {
                                                      "id": 198,
                                                      "name": "coef0",
                                                      "description": "对于poly和sigmoid有用。",
                                                      "sequence": 2,
                                                      "label": "coef0",
                                                      "default_value": "0",
                                                      "value_type_code": "float",
                                                      "value_type_name": "浮点数",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "slider",
                                                      "ui_type_name": "slider",
                                                      "ui_config": {
                                                          "min": 0,
                                                          "max": 999999,
                                                          "step": 0.01
                                                      },
                                                      "section_sequence": 2
                                                  },
                                                  {
                                                      "id": 199,
                                                      "name": "tol",
                                                      "description": "停止训练误差值大小。",
                                                      "sequence": 3,
                                                      "label": "tol",
                                                      "default_value": "0.001",
                                                      "value_type_code": "float",
                                                      "value_type_name": "浮点数",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "slider",
                                                      "ui_type_name": "slider",
                                                      "ui_config": {
                                                          "min": 0,
                                                          "max": 999999,
                                                          "step": 0.0001
                                                      },
                                                      "section_sequence": 2
                                                  },
                                                  {
                                                      "id": 200,
                                                      "name": "max_iter",
                                                      "description": "最大迭代次数。",
                                                      "sequence": 4,
                                                      "label": "max_iter",
                                                      "default_value": "100",
                                                      "value_type_code": "int",
                                                      "value_type_name": "整型",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "slider",
                                                      "ui_type_name": "slider",
                                                      "ui_config": {
                                                          "min": 1,
                                                          "max": 999999,
                                                          "step": 1
                                                      },
                                                      "section_sequence": 2
                                                  },
                                                  {
                                                      "id": 201,
                                                      "name": "random_state",
                                                      "description": "数据洗牌时的种子值。",
                                                      "sequence": 5,
                                                      "label": "random_state",
                                                      "default_value": "116",
                                                      "value_type_code": "int",
                                                      "value_type_name": "整型",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "input",
                                                      "ui_type_name": "input",
                                                      "ui_config": null,
                                                      "section_sequence": 2
                                                  },
                                                  {
                                                      "id": 202,
                                                      "name": "decision_function_shape",
                                                      "description": "包括ovo，ovr，None。",
                                                      "sequence": 6,
                                                      "label": "decision_function_shape",
                                                      "default_value": "None",
                                                      "value_type_code": "string",
                                                      "value_type_name": "字符串",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "radio",
                                                      "ui_type_name": "radio",
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                                                          "options": [
                                                              {
                                                                  "label": "ovo",
                                                                  "value": "ovo"
                                                              },
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                                                                  "label": "ovr",
                                                                  "value": "ovr"
                                                              }
                                                          ]
                                                      },
                                                      "section_sequence": 2
                                                  }
                                              ]
                                          }
                                      ]
                                  }
                              },
                              "tags": [
                                  {
                                      "id": 172,
                                      "tag_name": "支持向量机",
                                      "create_time": "2023-07-10 19:19:48",
                                      "tag_id": 105
                                  },
                                  {
                                      "id": 173,
                                      "tag_name": "二分类模型",
                                      "create_time": "2023-07-10 19:19:48",
                                      "tag_id": 106
                                  }
                              ],
                              "storages": {
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                                  "model": false,
                                  "data": false
                              },
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                              },
                              "downstreams": {
                                  "except": [
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                                  "only": null
                              },
                              "category_name": "binary_classification",
                              "label": "SVM二分类模型"
                          },
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                          "is_delete": false,
                          "delete_ts": null,
                          "delete_time": null,
                          "source_type_code": "official",
                          "source_type_name": "官方"
                      }
                  ],
                  "resources_total": 3
              },
              {
                  "id": 604,
                  "name": "multiple_classification",
                  "sequence": 4,
                  "description": "多分类",
                  "create_ts": 1645515710,
                  "create_time": "2022-02-22 15:41:50",
                  "is_enable": true,
                  "nodes": [],
                  "resources": [
                      {
                          "id": 38,
                          "name": "multiple_classification_knn_model",
                          "description": [
                              "KNeighborsClassifier 是一种基于最近邻的分类算法，即对于一个测试数据点，选择离它最近的 k 个训练数据点，并将其标签决策作为该测试数据点的预测标签。",
                              "该算法对于非线性和复杂的决策边界具有很好的鲁棒性。"
                          ],
                          "create_ts": 1688564534,
                          "create_time": "2023-07-05 21:42:14",
                          "update_ts": 1688987989,
                          "update_time": "2023-07-10 19:19:49",
                          "label": "KNN多分类模型",
                          "icon": "",
                          "category_id": 604,
                          "is_enable": true,
                          "operator": {
                              "id": 92,
                              "name": "multiple_classification_knn_model",
                              "description": [
                                  "KNeighborsClassifier 是一种基于最近邻的分类算法，即对于一个测试数据点，选择离它最近的 k 个训练数据点，并将其标签决策作为该测试数据点的预测标签。",
                                  "该算法对于非线性和复杂的决策边界具有很好的鲁棒性。"
                              ],
                              "create_ts": 1688987989,
                              "create_time": "2023-07-10 19:19:49",
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                              "output_num": 1,
                              "icon": "",
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                              "doc_url": "docs/canvas_operator/machine_learning/multiple_classification/multiple_classification_knn_model",
                              "version": "1.0.1",
                              "is_enable": true,
                              "template_id": 38,
                              "package_label": "sklearn.neighbors",
                              "function_label": "KNeighborsClassifier",
                              "run_function": "run",
                              "run_filepath": "main.py",
                              "language_name": "python",
                              "framework_name": null,
                              "stage_name": "开发",
                              "language_code": "python",
                              "framework_code": null,
                              "stage_code": "dev",
                              "inputs": [],
                              "outputs": [
                                  {
                                      "id": 173,
                                      "name": "model",
                                      "description": [
                                          "已构建的模型对象"
                                      ],
                                      "sequence": 1,
                                      "value_type_code": "model",
                                      "value_type_name": "model",
                                      "label": "模型对象"
                                  }
                              ],
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                                  "default": {
                                      "label": "默认",
                                      "results": []
                                  },
                                  "runtime": {
                                      "label": "运行期间",
                                      "results": []
                                  },
                                  "framework": {
                                      "label": "框架",
                                      "results": []
                                  },
                                  "section": {
                                      "label": "自定义",
                                      "results": [
                                          {
                                              "label": "模型参数",
                                              "results": [
                                                  {
                                                      "id": 234,
                                                      "name": "n_neighbors",
                                                      "description": "用于kneighbors查询的默认邻居的数量。",
                                                      "sequence": 1,
                                                      "label": "n_neighbors",
                                                      "default_value": "5",
                                                      "value_type_code": "int",
                                                      "value_type_name": "整型",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "inputNumber",
                                                      "ui_type_name": "inputNumber",
                                                      "ui_config": {
                                                          "min": 0,
                                                          "max": 999999,
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                                                      },
                                                      "section_sequence": 1
                                                  },
                                                  {
                                                      "id": 235,
                                                      "name": "weights",
                                                      "description": "用于预测的权重函数。uniform统一的权重.在每一个邻居区域里的点的权重都是一样的;distance权重点等于他们距离的倒数。使用此函数，更近的邻居对于所预测的点的影响更大;callable，一个用户自定义的方法，此方法接收一个距离的数组，然后返回一个相同形状并且包含权重的数组。",
                                                      "sequence": 2,
                                                      "label": "weights",
                                                      "default_value": "uniform",
                                                      "value_type_code": "string",
                                                      "value_type_name": "字符串",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "radio",
                                                      "ui_type_name": "radio",
                                                      "ui_config": {
                                                          "options": [
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                                                                  "label": "uniform",
                                                                  "value": "uniform"
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                                                                  "label": "distance",
                                                                  "value": "distance"
                                                              }
                                                          ],
                                                          "custom": true
                                                      },
                                                      "section_sequence": 1
                                                  }
                                              ]
                                          },
                                          {
                                              "label": "调优参数",
                                              "results": [
                                                  {
                                                      "id": 236,
                                                      "name": "algorithm",
                                                      "description": "ball_tree是可以克服kd树高纬失效，其构造过程是以质心C和半径r分割样本空间，每个节点是一个超球体;kd_tree构造kd树存储数据以便对其进行快速检索的树形数据结构，kd树也就是数据结构中的二叉树。以中值切分构造的树，每个结点是一个超矩形，在维数小于20时效率高;brute使用暴力搜索.也就是线性扫描，当训练集很大时，计算非常耗时;auto会基于传入fit方法的内容，选择最合适的算法。",
                                                      "sequence": 1,
                                                      "label": "algorithm",
                                                      "default_value": "auto",
                                                      "value_type_code": "string",
                                                      "value_type_name": "字符串",
                                                      "is_required": true,
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                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "radio",
                                                      "ui_type_name": "radio",
                                                      "ui_config": {
                                                          "options": [
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                                                                  "label": "auto",
                                                                  "value": "auto"
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                                                              {
                                                                  "label": "ball_tree",
                                                                  "value": "ball_tree"
                                                              },
                                                              {
                                                                  "label": "kd_tree",
                                                                  "value": "kd_tree"
                                                              },
                                                              {
                                                                  "label": "brute",
                                                                  "value": "brute"
                                                              }
                                                          ]
                                                      },
                                                      "section_sequence": 2
                                                  },
                                                  {
                                                      "id": 237,
                                                      "name": "leaf_size",
                                                      "description": "传入BallTree或者KDTree算法的叶子数量。此参数会影响构建、查询BallTree或者KDTree的速度，以及存储BallTree或者KDTree所需要的内存大小。此可选参数根据是否是问题所需选择性使用。",
                                                      "sequence": 2,
                                                      "label": "leaf_size",
                                                      "default_value": "30",
                                                      "value_type_code": "int",
                                                      "value_type_name": "整型",
                                                      "is_required": true,
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                                                  }
                                              ]
                                          }
                                      ]
                                  }
                              },
                              "tags": [
                                  {
                                      "id": 187,
                                      "tag_name": "多分类",
                                      "create_time": "2023-07-10 19:19:49",
                                      "tag_id": 112
                                  },
                                  {
                                      "id": 186,
                                      "tag_name": "KNN模型",
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                                      "tag_id": 115
                                  }
                              ],
                              "storages": {
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                          "source_type_name": "官方"
                      },
                      {
                          "id": 39,
                          "name": "multiple_classification_logistic_regression_model",
                          "description": [
                              "LogisticRegression（逻辑回归）是一种基于线性回归的分类算法，主要应用于二分类问题。",
                              "其核心思想是利用 sigmoid 函数将线性方程转化为对数几率形式，并可以拟合一个概率模型来预测样本属于某个类别的概率。"
                          ],
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                          "create_time": "2023-07-05 21:42:15",
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                          "update_time": "2023-07-10 19:19:49",
                          "label": "逻辑回归多分类模型",
                          "icon": "",
                          "category_id": 604,
                          "is_enable": true,
                          "operator": {
                              "id": 93,
                              "name": "multiple_classification_logistic_regression_model",
                              "description": [
                                  "LogisticRegression（逻辑回归）是一种基于线性回归的分类算法，主要应用于二分类问题。",
                                  "其核心思想是利用 sigmoid 函数将线性方程转化为对数几率形式，并可以拟合一个概率模型来预测样本属于某个类别的概率。"
                              ],
                              "create_ts": 1688987989,
                              "create_time": "2023-07-10 19:19:49",
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                              "update_time": "2023-07-10 19:19:49",
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                              "category_id": 604,
                              "doc_url": "docs/canvas_operator/machine_learning/multiple_classification/multiple_classification_logistic_regression_model",
                              "version": "1.0.1",
                              "is_enable": true,
                              "template_id": 39,
                              "package_label": "sklearn.linear_model",
                              "function_label": "LogisticRegression",
                              "run_function": "run",
                              "run_filepath": "main.py",
                              "language_name": "python",
                              "framework_name": null,
                              "stage_name": "开发",
                              "language_code": "python",
                              "framework_code": null,
                              "stage_code": "dev",
                              "inputs": [],
                              "outputs": [
                                  {
                                      "id": 174,
                                      "name": "model",
                                      "description": [
                                          "已构建模型对象"
                                      ],
                                      "sequence": 1,
                                      "value_type_code": "model",
                                      "value_type_name": "model",
                                      "label": "模型对象"
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                              ],
                              "configs": {
                                  "default": {
                                      "label": "默认",
                                      "results": []
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                                  "runtime": {
                                      "label": "运行期间",
                                      "results": []
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                                  "framework": {
                                      "label": "框架",
                                      "results": []
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                                      "label": "自定义",
                                      "results": [
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                                              "label": "模型参数",
                                              "results": [
                                                  {
                                                      "id": 238,
                                                      "name": "penalty",
                                                      "description": "netton-cg,sag,lbfgs只支持l2。若选择l2正则化还是过拟合，可考虑l1正则化。若模型特征非常多，一些不重要的特征系数归零，让模型系数化，使用’l1’正则化。",
                                                      "sequence": 1,
                                                      "label": "penalty",
                                                      "default_value": "l2",
                                                      "value_type_code": "string",
                                                      "value_type_name": "字符串",
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                                                      "is_enable": true,
                                                      "ui_type_code": "radio",
                                                      "ui_type_name": "radio",
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                                                          "options": [
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                                                                  "label": "l1",
                                                                  "value": "l1"
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                                                                  "label": "l2",
                                                                  "value": "l2"
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                                                          ]
                                                      },
                                                      "section_sequence": 1
                                                  },
                                                  {
                                                      "id": 239,
                                                      "name": "tol",
                                                      "description": "优化算法停止的条件。当迭代前后的函数差值小于等于tol时就停止。",
                                                      "sequence": 2,
                                                      "label": "tol",
                                                      "default_value": "0.0001",
                                                      "value_type_code": "float",
                                                      "value_type_name": "浮点数",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "inputNumber",
                                                      "ui_type_name": "inputNumber",
                                                      "ui_config": {
                                                          "min": 0,
                                                          "max": 9999,
                                                          "step": 0.0001
                                                      },
                                                      "section_sequence": 1
                                                  },
                                                  {
                                                      "id": 240,
                                                      "name": "C",
                                                      "description": "值越小，正则化越强。",
                                                      "sequence": 3,
                                                      "label": "C",
                                                      "default_value": "1",
                                                      "value_type_code": "float",
                                                      "value_type_name": "浮点数",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "inputNumber",
                                                      "ui_type_name": "inputNumber",
                                                      "ui_config": {
                                                          "min": 0,
                                                          "max": 1,
                                                          "step": 0.001
                                                      },
                                                      "section_sequence": 1
                                                  },
                                                  {
                                                      "id": 241,
                                                      "name": "fit_intercept",
                                                      "description": "选择逻辑回归模型中是否会有常数项b。",
                                                      "sequence": 4,
                                                      "label": "fit_intercept",
                                                      "default_value": "True",
                                                      "value_type_code": "string",
                                                      "value_type_name": "字符串",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "radio",
                                                      "ui_type_name": "radio",
                                                      "ui_config": {
                                                          "options": [
                                                              {
                                                                  "label": "True",
                                                                  "value": "True"
                                                              },
                                                              {
                                                                  "label": "False",
                                                                  "value": "False"
                                                              }
                                                          ]
                                                      },
                                                      "section_sequence": 1
                                                  }
                                              ]
                                          },
                                          {
                                              "label": "调优参数",
                                              "results": [
                                                  {
                                                      "id": 242,
                                                      "name": "class_weight",
                                                      "description": "balanced,类库根据训练样本量来计算权重。某种类型的样本量越多，则权重越低。也支持自定义。",
                                                      "sequence": 1,
                                                      "label": "class_weight",
                                                      "default_value": "balanced",
                                                      "value_type_code": "string",
                                                      "value_type_name": "字符串",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "radio",
                                                      "ui_type_name": "radio",
                                                      "ui_config": {
                                                          "options": [
                                                              {
                                                                  "label": "balanced",
                                                                  "value": "balanced"
                                                              }
                                                          ],
                                                          "custom": true
                                                      },
                                                      "section_sequence": 2
                                                  },
                                                  {
                                                      "id": 243,
                                                      "name": "solver",
                                                      "description": "liblinear,使用坐标轴下降法来迭代优化损失函数。只支持OvR。lbfgs,拟牛顿法一种。利用损失函数二阶导数矩阵即海森矩阵来迭代优化损失函数。newton-cg也是牛顿法一种。sag，随机平均梯度下降。每次迭代仅仅用一部分的样本来计算梯度，适合于样本数据多。",
                                                      "sequence": 2,
                                                      "label": "solver",
                                                      "default_value": "liblinear",
                                                      "value_type_code": "string",
                                                      "value_type_name": "字符串",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "radio",
                                                      "ui_type_name": "radio",
                                                      "ui_config": {
                                                          "options": [
                                                              {
                                                                  "label": "liblinear",
                                                                  "value": "liblinear"
                                                              },
                                                              {
                                                                  "label": "lbfgs",
                                                                  "value": "lbfgs"
                                                              },
                                                              {
                                                                  "label": "newton - cg",
                                                                  "value": "newton - cg"
                                                              },
                                                              {
                                                                  "label": "sag",
                                                                  "value": "sag"
                                                              },
                                                              {
                                                                  "label": "saga",
                                                                  "value": "saga"
                                                              }
                                                          ]
                                                      },
                                                      "section_sequence": 2
                                                  },
                                                  {
                                                      "id": 244,
                                                      "name": "max_iter",
                                                      "description": "优化算法的迭代次数。",
                                                      "sequence": 3,
                                                      "label": "max_iter",
                                                      "default_value": "1000",
                                                      "value_type_code": "int",
                                                      "value_type_name": "整型",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "inputNumber",
                                                      "ui_type_name": "inputNumber",
                                                      "ui_config": {
                                                          "min": 0,
                                                          "max": 99999,
                                                          "step": 1
                                                      },
                                                      "section_sequence": 2
                                                  },
                                                  {
                                                      "id": 245,
                                                      "name": "multi_class",
                                                      "description": "multinomial即为MvM。若是二元逻辑回归，二者区别不大。",
                                                      "sequence": 4,
                                                      "label": "multi_class",
                                                      "default_value": "auto",
                                                      "value_type_code": "string",
                                                      "value_type_name": "字符串",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "radio",
                                                      "ui_type_name": "radio",
                                                      "ui_config": {
                                                          "options": [
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                                                                  "label": "ovr",
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                                                              {
                                                                  "label": "multinomial",
                                                                  "value": "multinomial"
                                                              },
                                                              {
                                                                  "label": "auto",
                                                                  "value": "auto"
                                                              }
                                                          ]
                                                      },
                                                      "section_sequence": 2
                                                  }
                                              ]
                                          }
                                      ]
                                  }
                              },
                              "tags": [
                                  {
                                      "id": 189,
                                      "tag_name": "多分类",
                                      "create_time": "2023-07-10 19:19:49",
                                      "tag_id": 112
                                  },
                                  {
                                      "id": 188,
                                      "tag_name": "逻辑回归多分类模型",
                                      "create_time": "2023-07-10 19:19:49",
                                      "tag_id": 116
                                  }
                              ],
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                              },
                              "upstreams": {
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                              },
                              "downstreams": {
                                  "except": [
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                                  "only": null
                              },
                              "category_name": "multiple_classification",
                              "label": "逻辑回归多分类模型"
                          },
                          "sequence": 0,
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                          "delete_ts": null,
                          "delete_time": null,
                          "source_type_code": "official",
                          "source_type_name": "官方"
                      },
                      {
                          "id": 35,
                          "name": "multiple_classification_Naive_Bayes_model",
                          "description": [
                              "MultinomialNB（多项式朴素贝叶斯）是一种朴素贝叶斯分类算法，适用于离散特征值的分类问题。",
                              "其核心思想是利用贝叶斯定理和独立特征假设，根据出现次数来计算每个类别的概率。"
                          ],
                          "create_ts": 1688564534,
                          "create_time": "2023-07-05 21:42:14",
                          "update_ts": 1688987988,
                          "update_time": "2023-07-10 19:19:48",
                          "label": "朴素贝叶斯多分类模型",
                          "icon": "",
                          "category_id": 604,
                          "is_enable": true,
                          "operator": {
                              "id": 89,
                              "name": "multiple_classification_Naive_Bayes_model",
                              "description": [
                                  "MultinomialNB（多项式朴素贝叶斯）是一种朴素贝叶斯分类算法，适用于离散特征值的分类问题。",
                                  "其核心思想是利用贝叶斯定理和独立特征假设，根据出现次数来计算每个类别的概率。"
                              ],
                              "create_ts": 1688987988,
                              "create_time": "2023-07-10 19:19:48",
                              "update_ts": 1688987988,
                              "update_time": "2023-07-10 19:19:48",
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                              "doc_url": "docs/canvas_operator/machine_learning/multiple_classification/multiple_classification_Naive_Bayes_model",
                              "version": "1.0.1",
                              "is_enable": true,
                              "template_id": 35,
                              "package_label": "sklearn.naive_bayes",
                              "function_label": "MultinomialNB",
                              "run_function": "run",
                              "run_filepath": "main.py",
                              "language_name": "python",
                              "framework_name": null,
                              "stage_name": "开发",
                              "language_code": "python",
                              "framework_code": null,
                              "stage_code": "dev",
                              "inputs": [],
                              "outputs": [
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                                      "id": 170,
                                      "name": "model",
                                      "description": [
                                          "已构建模型对象"
                                      ],
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                              },
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                          "description": [
                              "RandomForestClassifier（随机森林分类器）是一种基于决策树的集成学习算法，采用多个决策树相互竞争和协作的方式来进行分类。",
                              "其核心思想是通过构建不同的决策树来捕获数据中的不同方面，并通过加强泛化性能和减少过拟合来提高整个模型的性能。"
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                              "description": [
                                  "RandomForestClassifier（随机森林分类器）是一种基于决策树的集成学习算法，采用多个决策树相互竞争和协作的方式来进行分类。",
                                  "其核心思想是通过构建不同的决策树来捕获数据中的不同方面，并通过加强泛化性能和减少过拟合来提高整个模型的性能。"
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                              "language_code": "python",
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                                                      "name": "n_estimators",
                                                      "description": "森林中决策树的数量。",
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                                                      "description": "分裂节点所用的标准，可选“gini”, “entropy”，默认“gini”。",
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                                                      "label": "criterion",
                                                      "default_value": "gini",
                                                      "value_type_code": "string",
                                                      "value_type_name": "字符串",
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                                                  },
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                                                      "name": "max_depth",
                                                      "description": "树的最大深度。如果为None，则将节点展开，直到所有叶子都是纯净的(只有一个类)，或者直到所有叶子都包含少于min_samples_split个样本。",
                                                      "sequence": 3,
                                                      "label": "max_depth",
                                                      "default_value": "None",
                                                      "value_type_code": "int",
                                                      "value_type_name": "整型",
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                                                      "ui_type_code": "inputNumber",
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                                                      "id": 224,
                                                      "name": "max_features",
                                                      "description": "寻找最佳分割时要考虑的特征数量。包含sqrt，auto，log2，None。",
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                                                      "label": "max_features",
                                                      "default_value": "None",
                                                      "value_type_code": "string",
                                                      "value_type_name": "字符串",
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                                                      "is_visible": true,
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                                                      "is_enable": true,
                                                      "ui_type_code": "radio",
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                                                              {
                                                                  "label": "log2",
                                                                  "value": "log2"
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                                                      },
                                                      "section_sequence": 1
                                                  },
                                                  {
                                                      "id": 225,
                                                      "name": "class_weight",
                                                      "description": "支持用字典的形式传入自定义。默认balanced。",
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                                                      "label": "class_weight",
                                                      "default_value": "balanced",
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                              },
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                          "description": [
                              "SGDClassifier 是一种基于梯度下降的分类算法，包含了多个线性分类器的实现方法。",
                              "在处理大规模数据时，该算法可以快速地进行训练和预测，并且支持在线学习和增量训练。"
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                              "description": [
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                                  "在处理大规模数据时，该算法可以快速地进行训练和预测，并且支持在线学习和增量训练。"
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                                                      "sequence": 1,
                                                      "label": "loss",
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                                                                  "label": "modified_huber",
                                                                  "value": "modified_huber"
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                                                                  "label": "squared_hinge",
                                                                  "value": "squared_hinge"
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                                                                  "label": "perceptron",
                                                                  "value": "perceptron"
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                                                          ]
                                                      },
                                                      "section_sequence": 1
                                                  },
                                                  {
                                                      "id": 227,
                                                      "name": "penalty",
                                                      "description": "惩罚项。默认值为l2。包含l1，l2，elasticnet。",
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                                                      "label": "penalty",
                                                      "default_value": "l2",
                                                      "value_type_code": "string",
                                                      "value_type_name": "字符串",
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                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "radio",
                                                      "ui_type_name": "radio",
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                                                          "options": [
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                                                                  "label": "l2",
                                                                  "value": "l2"
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                                                              {
                                                                  "label": "elasticnet",
                                                                  "value": "elasticnet"
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                                                  {
                                                      "id": 228,
                                                      "name": "fit_intercept",
                                                      "description": "布尔值，是否估计截距，如果为假，认为数据已经中心化。",
                                                      "sequence": 3,
                                                      "label": "fit_intercept",
                                                      "default_value": "True",
                                                      "value_type_code": "string",
                                                      "value_type_name": "字符串",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "radio",
                                                      "ui_type_name": "radio",
                                                      "ui_config": {
                                                          "options": [
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                                                                  "label": "True",
                                                                  "value": "True"
                                                              },
                                                              {
                                                                  "label": "False",
                                                                  "value": "False"
                                                              }
                                                          ]
                                                      },
                                                      "section_sequence": 1
                                                  }
                                              ]
                                          },
                                          {
                                              "label": "调优参数",
                                              "results": [
                                                  {
                                                      "id": 229,
                                                      "name": "max_iter",
                                                      "description": "整数，可选的。迭代的最大次数，如果参数tol不是空，则默认值为1000。",
                                                      "sequence": 1,
                                                      "label": "max_iter",
                                                      "default_value": "1000",
                                                      "value_type_code": "int",
                                                      "value_type_name": "整型",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "inputNumber",
                                                      "ui_type_name": "inputNumber",
                                                      "ui_config": {
                                                          "min": 0,
                                                          "max": 99999,
                                                          "step": 1
                                                      },
                                                      "section_sequence": 2
                                                  },
                                                  {
                                                      "id": 230,
                                                      "name": "tol",
                                                      "description": "浮点数。训练结束的误差边界。当previous_loss - cur_loss < tol时，训练结束。默认值为0.001",
                                                      "sequence": 2,
                                                      "label": "tol",
                                                      "default_value": "0.001",
                                                      "value_type_code": "float",
                                                      "value_type_name": "浮点数",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "inputNumber",
                                                      "ui_type_name": "inputNumber",
                                                      "ui_config": {
                                                          "min": 0,
                                                          "max": 9999,
                                                          "step": 0.0001
                                                      },
                                                      "section_sequence": 2
                                                  },
                                                  {
                                                      "id": 231,
                                                      "name": "shuffle",
                                                      "description": "布尔值，可选的。每轮迭代后是否打乱数据的顺序，默认为True。",
                                                      "sequence": 3,
                                                      "label": "shuffle",
                                                      "default_value": "True",
                                                      "value_type_code": "string",
                                                      "value_type_name": "字符串",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "radio",
                                                      "ui_type_name": "radio",
                                                      "ui_config": {
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                                                              {
                                                                  "label": "True",
                                                                  "value": "True"
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                                                              {
                                                                  "label": "False",
                                                                  "value": "False"
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                                                          ]
                                                      },
                                                      "section_sequence": 2
                                                  },
                                                  {
                                                      "id": 232,
                                                      "name": "learning_rate",
                                                      "description": "学习速率的策略。",
                                                      "sequence": 4,
                                                      "label": "learning_rate",
                                                      "default_value": "optimal",
                                                      "value_type_code": "string",
                                                      "value_type_name": "字符串",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "radio",
                                                      "ui_type_name": "radio",
                                                      "ui_config": {
                                                          "options": [
                                                              {
                                                                  "label": "constant",
                                                                  "value": "constant"
                                                              },
                                                              {
                                                                  "label": "optimal",
                                                                  "value": "optimal"
                                                              },
                                                              {
                                                                  "label": "invscaling",
                                                                  "value": "invscaling"
                                                              }
                                                          ]
                                                      },
                                                      "section_sequence": 2
                                                  },
                                                  {
                                                      "id": 233,
                                                      "name": "class_weight",
                                                      "description": "balanced,类库根据训练样本量来计算权重。某种类型的样本量越多，则权重越低。也支持自定义。",
                                                      "sequence": 5,
                                                      "label": "class_weight",
                                                      "default_value": "balanced",
                                                      "value_type_code": "string",
                                                      "value_type_name": "字符串",
                                                      "is_required": true,
                                                      "is_visible": true,
                                                      "is_editable": true,
                                                      "is_enable": true,
                                                      "ui_type_code": "radio",
                                                      "ui_type_name": "radio",
                                                      "ui_config": {
                                                          "options": [
                                                              {
                                                                  "label": "balanced",
                                                                  "value": "balanced"
                                                              }
                                                          ],
                                                          "custom": true
                                                      },
                                                      "section_sequence": 2
                                                  }
                                              ]
                                          }
                                      ]
                                  }
                              },
                              "tags": [
                                  {
                                      "id": 185,
                                      "tag_name": "多分类",
                                      "create_time": "2023-07-10 19:19:49",
                                      "tag_id": 112
                                  },
                                  {
                                      "id": 184,
                                      "tag_name": "SGD模型",
                                      "create_time": "2023-07-10 19:19:49",
                                      "tag_id": 114
                                  }
                              ],
                              "storages": {
                                  "artifact": false,
                                  "model": false,
                                  "data": false
                              },
                              "upstreams": {
                                  "except": [
                                      "data_visualization",
                                      "evaluate_model"
                                  ],
                                  "only": null
                              },
                              "downstreams": {
                                  "except": [
                                      "datasource"
                                  ],
                                  "only": null
                              },
                              "category_name": "multiple_classification",
                              "label": "SGD多分类模型"
                          },
                          "sequence": 0,
                          "is_delete": false,
                          "delete_ts": null,
                          "delete_time": null,
                          "source_type_code": "official",
                          "source_type_name": "官方"
                      }
                  ],
                  "resources_total": 5
              }
          ],
          "resources": [],
          "resources_total": 16
      },
      {
          "id": 8,
          "name": "platform_function",
          "sequence": 8,
          "description": "平台功能",
          "create_ts": 1645515710,
          "create_time": "2022-02-22 15:41:50",
          "is_enable": true,
          "nodes": [],
          "resources": [
              {
                  "id": 45,
                  "name": "evaluate_model",
                  "description": [
                      "进行模型评估节点。"
                  ],
                  "create_ts": 1688564535,
                  "create_time": "2023-07-05 21:42:15",
                  "update_ts": 1688987990,
                  "update_time": "2023-07-10 19:19:50",
                  "label": "评估模型",
                  "icon": "",
                  "category_id": 8,
                  "is_enable": true,
                  "operator": {
                      "id": 99,
                      "name": "evaluate_model",
                      "description": [
                          "进行模型评估节点。"
                      ],
                      "create_ts": 1688987990,
                      "create_time": "2023-07-10 19:19:50",
                      "update_ts": 1688987990,
                      "update_time": "2023-07-10 19:19:50",
                      "input_num": 1,
                      "output_num": 1,
                      "icon": "",
                      "category_id": 8,
                      "doc_url": "docs/canvas_operator/model_evaluation/clustering",
                      "version": "1.0.1",
                      "is_enable": true,
                      "template_id": 45,
                      "package_label": "scikit-learn",
                      "function_label": "GradientBoostingClassifier",
                      "run_function": "run",
                      "run_filepath": "main.py",
                      "language_name": "python",
                      "framework_name": null,
                      "stage_name": "开发",
                      "language_code": "python",
                      "framework_code": null,
                      "stage_code": "dev",
                      "inputs": [
                          {
                              "id": 180,
                              "name": "input_tables",
                              "description": [
                                  "预测结果数据集"
                              ],
                              "sequence": 1,
                              "value_type_code": "dataframe",
                              "value_type_name": "数据帧",
                              "label": "预测结果数据集"
                          }
                      ],
                      "outputs": [
                          {
                              "id": 181,
                              "name": "resultdata",
                              "description": [
                                  "模型评估结果"
                              ],
                              "sequence": 1,
                              "value_type_code": "list",
                              "value_type_name": "列表",
                              "label": "模型评估结果"
                          }
                      ],
                      "configs": {
                          "default": {
                              "label": "默认",
                              "results": [
                                  {
                                      "label": "默认",
                                      "results": [
                                          {
                                              "id": 272,
                                              "name": "input_keys",
                                              "description": [
                                                  "模型对象。"
                                              ],
                                              "sequence": 1,
                                              "label": "模型对象",
                                              "default_value": null,
                                              "value_type_code": "list",
                                              "value_type_name": "列表",
                                              "is_required": false,
                                              "is_visible": true,
                                              "is_editable": true,
                                              "is_enable": true,
                                              "ui_type_code": "textarea",
                                              "ui_type_name": "textarea",
                                              "ui_config": null,
                                              "section_sequence": 0
                                          }
                                      ]
                                  }
                              ]
                          },
                          "runtime": {
                              "label": "运行期间",
                              "results": []
                          },
                          "framework": {
                              "label": "框架",
                              "results": []
                          },
                          "section": {
                              "label": "自定义",
                              "results": []
                          }
                      },
                      "tags": [
                          {
                              "id": 199,
                              "tag_name": "评估模型",
                              "create_time": "2023-07-10 19:19:50",
                              "tag_id": 122
                          }
                      ],
                      "storages": {
                          "artifact": true,
                          "model": false,
                          "data": false
                      },
                      "upstreams": {
                          "except": [
                              "data_visualization",
                              "evaluate_model"
                          ],
                          "only": null
                      },
                      "downstreams": {
                          "except": [
                              "datasource"
                          ],
                          "only": null
                      },
                      "category_name": "platform_function",
                      "label": "评估模型"
                  },
                  "sequence": 0,
                  "is_delete": false,
                  "delete_ts": null,
                  "delete_time": null,
                  "source_type_code": "official",
                  "source_type_name": "官方"
              },
              {
                  "id": 46,
                  "name": "predict_model",
                  "description": [
                      "进行模型预测节点。"
                  ],
                  "create_ts": 1688564535,
                  "create_time": "2023-07-05 21:42:15",
                  "update_ts": 1688987990,
                  "update_time": "2023-07-10 19:19:50",
                  "label": "预测模型-分类及回归",
                  "icon": "",
                  "category_id": 8,
                  "is_enable": true,
                  "operator": {
                      "id": 100,
                      "name": "predict_model",
                      "description": [
                          "进行模型预测节点。"
                      ],
                      "create_ts": 1688987990,
                      "create_time": "2023-07-10 19:19:50",
                      "update_ts": 1688987990,
                      "update_time": "2023-07-10 19:19:50",
                      "input_num": 2,
                      "output_num": 1,
                      "icon": "",
                      "category_id": 8,
                      "doc_url": "",
                      "version": "1.0.1",
                      "is_enable": true,
                      "template_id": 46,
                      "package_label": "scikit-learn",
                      "function_label": "GradientBoostingClassifier",
                      "run_function": "run",
                      "run_filepath": "main.py",
                      "language_name": "python",
                      "framework_name": null,
                      "stage_name": "开发",
                      "language_code": "python",
                      "framework_code": null,
                      "stage_code": "dev",
                      "inputs": [
                          {
                              "id": 182,
                              "name": "model",
                              "description": [
                                  "模型对象"
                              ],
                              "sequence": 1,
                              "value_type_code": "model",
                              "value_type_name": "model",
                              "label": "已构建的模型对象"
                          },
                          {
                              "id": 183,
                              "name": "testTable",
                              "description": [
                                  "测试数据集"
                              ],
                              "sequence": 2,
                              "value_type_code": "dataframe",
                              "value_type_name": "数据帧",
                              "label": "测试数据集"
                          }
                      ],
                      "outputs": [
                          {
                              "id": 184,
                              "name": "resultdata",
                              "description": [
                                  "模型预测结果"
                              ],
                              "sequence": 1,
                              "value_type_code": "dataframe",
                              "value_type_name": "数据帧",
                              "label": "模型预测结果"
                          }
                      ],
                      "configs": {
                          "default": {
                              "label": "默认",
                              "results": [
                                  {
                                      "label": "默认",
                                      "results": [
                                          {
                                              "id": 273,
                                              "name": "labelColName",
                                              "description": "作为标签的列。",
                                              "sequence": 1,
                                              "label": "目标列",
                                              "default_value": null,
                                              "value_type_code": "list",
                                              "value_type_name": "列表",
                                              "is_required": true,
                                              "is_visible": true,
                                              "is_editable": true,
                                              "is_enable": true,
                                              "ui_type_code": "dynamicParameter",
                                              "ui_type_name": "dynamicParameter",
                                              "ui_config": {
                                                  "input": "testTable"
                                              },
                                              "section_sequence": 0
                                          }
                                      ]
                                  }
                              ]
                          },
                          "runtime": {
                              "label": "运行期间",
                              "results": []
                          },
                          "framework": {
                              "label": "框架",
                              "results": []
                          },
                          "section": {
                              "label": "自定义",
                              "results": []
                          }
                      },
                      "tags": [
                          {
                              "id": 200,
                              "tag_name": "预测模型",
                              "create_time": "2023-07-10 19:19:50",
                              "tag_id": 123
                          }
                      ],
                      "storages": {
                          "artifact": false,
                          "model": false,
                          "data": false
                      },
                      "upstreams": {
                          "except": [
                              "data_visualization",
                              "evaluate_model"
                          ],
                          "only": null
                      },
                      "downstreams": {
                          "except": [
                              "datasource"
                          ],
                          "only": null
                      },
                      "category_name": "platform_function",
                      "label": "预测模型-分类及回归"
                  },
                  "sequence": 0,
                  "is_delete": false,
                  "delete_ts": null,
                  "delete_time": null,
                  "source_type_code": "official",
                  "source_type_name": "官方"
              },
              {
                  "id": 47,
                  "name": "predict_model_cluster",
                  "description": [
                      "进行模型预测节点。"
                  ],
                  "create_ts": 1688564535,
                  "create_time": "2023-07-05 21:42:15",
                  "update_ts": 1688987990,
                  "update_time": "2023-07-10 19:19:50",
                  "label": "预测模型-聚类",
                  "icon": "",
                  "category_id": 8,
                  "is_enable": true,
                  "operator": {
                      "id": 101,
                      "name": "predict_model_cluster",
                      "description": [
                          "进行模型预测节点。"
                      ],
                      "create_ts": 1688987990,
                      "create_time": "2023-07-10 19:19:50",
                      "update_ts": 1688987990,
                      "update_time": "2023-07-10 19:19:50",
                      "input_num": 2,
                      "output_num": 1,
                      "icon": "",
                      "category_id": 8,
                      "doc_url": "",
                      "version": "1.0.1",
                      "is_enable": true,
                      "template_id": 47,
                      "package_label": "scikit-learn",
                      "function_label": "GradientBoostingClassifier",
                      "run_function": "run",
                      "run_filepath": "main.py",
                      "language_name": "python",
                      "framework_name": null,
                      "stage_name": "开发",
                      "language_code": "python",
                      "framework_code": null,
                      "stage_code": "dev",
                      "inputs": [
                          {
                              "id": 185,
                              "name": "model",
                              "description": [
                                  "模型对象"
                              ],
                              "sequence": 1,
                              "value_type_code": "model",
                              "value_type_name": "model",
                              "label": "已构建的模型对象"
                          },
                          {
                              "id": 186,
                              "name": "testTable",
                              "description": [
                                  "测试数据集"
                              ],
                              "sequence": 2,
                              "value_type_code": "dataframe",
                              "value_type_name": "数据帧",
                              "label": "测试数据集"
                          }
                      ],
                      "outputs": [
                          {
                              "id": 187,
                              "name": "resultdata",
                              "description": [
                                  "模型预测结果"
                              ],
                              "sequence": 1,
                              "value_type_code": "dataframe",
                              "value_type_name": "数据帧",
                              "label": "模型预测结果"
                          }
                      ],
                      "configs": {
                          "default": {
                              "label": "默认",
                              "results": []
                          },
                          "runtime": {
                              "label": "运行期间",
                              "results": []
                          },
                          "framework": {
                              "label": "框架",
                              "results": []
                          },
                          "section": {
                              "label": "自定义",
                              "results": []
                          }
                      },
                      "tags": [
                          {
                              "id": 201,
                              "tag_name": "预测模型",
                              "create_time": "2023-07-10 19:19:50",
                              "tag_id": 123
                          }
                      ],
                      "storages": {
                          "artifact": false,
                          "model": false,
                          "data": false
                      },
                      "upstreams": {
                          "except": [
                              "data_visualization",
                              "evaluate_model"
                          ],
                          "only": null
                      },
                      "downstreams": {
                          "except": [
                              "datasource"
                          ],
                          "only": null
                      },
                      "category_name": "platform_function",
                      "label": "预测模型-聚类"
                  },
                  "sequence": 0,
                  "is_delete": false,
                  "delete_ts": null,
                  "delete_time": null,
                  "source_type_code": "official",
                  "source_type_name": "官方"
              },
              {
                  "id": 48,
                  "name": "train_model",
                  "description": [
                      "进行模型训练节点。"
                  ],
                  "create_ts": 1688564535,
                  "create_time": "2023-07-05 21:42:15",
                  "update_ts": 1688987990,
                  "update_time": "2023-07-10 19:19:50",
                  "label": "训练模型-分类及回归",
                  "icon": "",
                  "category_id": 8,
                  "is_enable": true,
                  "operator": {
                      "id": 102,
                      "name": "train_model",
                      "description": [
                          "进行模型训练节点。"
                      ],
                      "create_ts": 1688987990,
                      "create_time": "2023-07-10 19:19:50",
                      "update_ts": 1688987990,
                      "update_time": "2023-07-10 19:19:50",
                      "input_num": 2,
                      "output_num": 1,
                      "icon": "",
                      "category_id": 8,
                      "doc_url": "",
                      "version": "1.0.1",
                      "is_enable": true,
                      "template_id": 48,
                      "package_label": "scikit-learn",
                      "function_label": "GradientBoostingClassifier",
                      "run_function": "run",
                      "run_filepath": "main.py",
                      "language_name": "python",
                      "framework_name": null,
                      "stage_name": "开发",
                      "language_code": "python",
                      "framework_code": null,
                      "stage_code": "dev",
                      "inputs": [
                          {
                              "id": 188,
                              "name": "model",
                              "description": [
                                  "模型对象"
                              ],
                              "sequence": 1,
                              "value_type_code": "model",
                              "value_type_name": "model",
                              "label": "已构建的模型对象"
                          },
                          {
                              "id": 189,
                              "name": "trainTable",
                              "description": [
                                  "训练数据集"
                              ],
                              "sequence": 2,
                              "value_type_code": "dataframe",
                              "value_type_name": "数据帧",
                              "label": "训练数据集"
                          }
                      ],
                      "outputs": [
                          {
                              "id": 190,
                              "name": "model",
                              "description": [
                                  "模型对象"
                              ],
                              "sequence": 1,
                              "value_type_code": "model",
                              "value_type_name": "model",
                              "label": "训练后的模型"
                          }
                      ],
                      "configs": {
                          "default": {
                              "label": "默认",
                              "results": [
                                  {
                                      "label": "默认",
                                      "results": [
                                          {
                                              "id": 274,
                                              "name": "labelColName",
                                              "description": "作为标签的列。",
                                              "sequence": 1,
                                              "label": "目标列",
                                              "default_value": null,
                                              "value_type_code": "list",
                                              "value_type_name": "列表",
                                              "is_required": true,
                                              "is_visible": true,
                                              "is_editable": true,
                                              "is_enable": true,
                                              "ui_type_code": "dynamicParameter",
                                              "ui_type_name": "dynamicParameter",
                                              "ui_config": {
                                                  "input": "trainTable"
                                              },
                                              "section_sequence": 0
                                          }
                                      ]
                                  }
                              ]
                          },
                          "runtime": {
                              "label": "运行期间",
                              "results": []
                          },
                          "framework": {
                              "label": "框架",
                              "results": []
                          },
                          "section": {
                              "label": "自定义",
                              "results": []
                          }
                      },
                      "tags": [
                          {
                              "id": 202,
                              "tag_name": "训练模型",
                              "create_time": "2023-07-10 19:19:50",
                              "tag_id": 124
                          }
                      ],
                      "storages": {
                          "artifact": false,
                          "model": true,
                          "data": false
                      },
                      "upstreams": {
                          "except": [
                              "data_visualization",
                              "evaluate_model"
                          ],
                          "only": null
                      },
                      "downstreams": {
                          "except": [
                              "datasource"
                          ],
                          "only": null
                      },
                      "category_name": "platform_function",
                      "label": "训练模型-分类及回归"
                  },
                  "sequence": 0,
                  "is_delete": false,
                  "delete_ts": null,
                  "delete_time": null,
                  "source_type_code": "official",
                  "source_type_name": "官方"
              },
              {
                  "id": 49,
                  "name": "train_model_cluster",
                  "description": [
                      "进行模型训练节点。"
                  ],
                  "create_ts": 1688564535,
                  "create_time": "2023-07-05 21:42:15",
                  "update_ts": 1688987990,
                  "update_time": "2023-07-10 19:19:50",
                  "label": "训练模型-聚类",
                  "icon": "",
                  "category_id": 8,
                  "is_enable": true,
                  "operator": {
                      "id": 103,
                      "name": "train_model_cluster",
                      "description": [
                          "进行模型训练节点。"
                      ],
                      "create_ts": 1688987990,
                      "create_time": "2023-07-10 19:19:50",
                      "update_ts": 1688987990,
                      "update_time": "2023-07-10 19:19:50",
                      "input_num": 2,
                      "output_num": 1,
                      "icon": "",
                      "category_id": 8,
                      "doc_url": "",
                      "version": "1.0.1",
                      "is_enable": true,
                      "template_id": 49,
                      "package_label": "scikit-learn",
                      "function_label": "GradientBoostingClassifier",
                      "run_function": "run",
                      "run_filepath": "main.py",
                      "language_name": "python",
                      "framework_name": null,
                      "stage_name": "开发",
                      "language_code": "python",
                      "framework_code": null,
                      "stage_code": "dev",
                      "inputs": [
                          {
                              "id": 191,
                              "name": "model",
                              "description": [
                                  "模型对象"
                              ],
                              "sequence": 1,
                              "value_type_code": "model",
                              "value_type_name": "model",
                              "label": "已构建的模型对象"
                          },
                          {
                              "id": 192,
                              "name": "trainTable",
                              "description": [
                                  "训练数据集"
                              ],
                              "sequence": 2,
                              "value_type_code": "dataframe",
                              "value_type_name": "数据帧",
                              "label": "训练数据集"
                          }
                      ],
                      "outputs": [
                          {
                              "id": 193,
                              "name": "model",
                              "description": [
                                  "模型对象"
                              ],
                              "sequence": 1,
                              "value_type_code": "model",
                              "value_type_name": "model",
                              "label": "训练后的模型"
                          }
                      ],
                      "configs": {
                          "default": {
                              "label": "默认",
                              "results": []
                          },
                          "runtime": {
                              "label": "运行期间",
                              "results": []
                          },
                          "framework": {
                              "label": "框架",
                              "results": []
                          },
                          "section": {
                              "label": "自定义",
                              "results": []
                          }
                      },
                      "tags": [
                          {
                              "id": 203,
                              "tag_name": "训练模型",
                              "create_time": "2023-07-10 19:19:50",
                              "tag_id": 124
                          }
                      ],
                      "storages": {
                          "artifact": false,
                          "model": true,
                          "data": false
                      },
                      "upstreams": {
                          "except": [
                              "data_visualization",
                              "evaluate_model"
                          ],
                          "only": null
                      },
                      "downstreams": {
                          "except": [
                              "datasource"
                          ],
                          "only": null
                      },
                      "category_name": "platform_function",
                      "label": "训练模型-聚类"
                  },
                  "sequence": 0,
                  "is_delete": false,
                  "delete_ts": null,
                  "delete_time": null,
                  "source_type_code": "official",
                  "source_type_name": "官方"
              }
          ],
          "resources_total": 5
      }
  ]
}
export const operatorIconConfig = {
  '数据读取': {
    'icon': 'wenjianduqu',
    'fill': '#66CC99'
  },
  '数据预处理': {
    'icon': 'yuchuli',
    'fill': '#6699FF'
  },
  '数据可视化': {
    'icon': '_keshihua',
    'fill': '#993333'
  },
  '统计分析': {
    'icon': 'tongjifenxi',
    'fill': '#CC3399'
  },
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  '模型评估': {
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  '平台功能': {
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    'fill': '#333333'
  },
  '模型训练': {
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  '模型预测': {
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}
